{"meta":{"query_hash":"c4fa1a0a7c51","filters":{"venue":"International Journal for Population Data Science"},"cohort_total":810,"direct_labels_cover":7,"predictions_cover":810,"exported":810,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/c4fa1a0a7c51","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+for+Population+Data+Science"},"results":[{"id":"W2605406864","doi":"10.23889/ijpds.v1i1.280","title":"Social outcomes associated with alcohol-related diagnoses: a population-based analysis using linked administrative data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Socioeconomic status; Receipt; Population; Medicine; Demography; Residence; Census; Gerontology; Environmental health; Business; Sociology","score_opus":0.4067627797782062,"score_gpt":0.5926869374173978,"score_spread":0.18592415763919157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605406864","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.988375,0.000009719529,0.0048540737,0.0015719807,0.0016539595,0.0004964114,0.0028686703,0.000045689994,0.00012449842],"genre_scores_gemma":[0.99025524,0.000005436227,0.0017655072,0.00010593019,0.0003991831,0.000016164973,0.007322707,0.000020324653,0.000109493485],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99637747,0.00022485737,0.00090182765,0.00062632776,0.001425651,0.00044384145],"domain_scores_gemma":[0.9943507,0.00070847024,0.0022242547,0.0010959491,0.0014504415,0.00017018724],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003147156,0.00019892886,0.0005206159,0.00048243112,0.007340901,0.0007638052,0.004477004,0.00016236112,0.00013384016],"category_scores_gemma":[0.0067576477,0.00015927287,0.00010371331,0.0005186585,0.00026562312,0.0042366544,0.0007171937,0.00042691827,0.0000054086095],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005333388,0.000082018574,0.99516183,0.0000042677148,0.0005453398,0.000008581641,0.0009237246,0.00048115355,0.000009163281,0.001697973,0.000037540696,0.0009950987],"study_design_scores_gemma":[0.0011628608,0.000021334059,0.89516896,0.00010060269,0.00034121654,3.915331e-7,0.0014680056,0.10064266,0.0000010484998,0.0007862063,0.00011690603,0.00018979081],"about_ca_topic_score_codex":0.0051196516,"about_ca_topic_score_gemma":0.0198135,"teacher_disagreement_score":0.10016151,"about_ca_system_score_codex":0.00051560753,"about_ca_system_score_gemma":0.00091278774,"threshold_uncertainty_score":0.9980723},"labels":[],"label_agreement":null},{"id":"W2605433059","doi":"10.23889/ijpds.v1i1.140","title":"Using Linked Administrative Data to Examine the Educational Outcomes of Children in Care in Manitoba","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child Welfare and Adoption","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Receipt; Welfare; Medicine; Population; Family income; Health care; Family medicine; Multivariate analysis; Pediatrics; Demography; Nursing; Environmental health","score_opus":0.31139550343839073,"score_gpt":0.515297516841514,"score_spread":0.2039020134031233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605433059","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98553663,0.000025073954,0.0002998303,0.011630701,0.0013299566,0.00035327845,0.0005508572,0.0000026457478,0.00027099455],"genre_scores_gemma":[0.99614155,0.00001977801,0.0028646619,0.000114981645,0.00044117542,0.0000026635796,0.00038415304,0.0000033186288,0.00002772336],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984304,0.00005073734,0.00034017907,0.00026840984,0.00075633544,0.0001539693],"domain_scores_gemma":[0.9984912,0.00012749243,0.0003542416,0.0006217885,0.0003443394,0.000060929462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018546074,0.000063188745,0.000094705945,0.00022772608,0.00084669684,0.00046381762,0.004555432,0.000027014019,0.000019157367],"category_scores_gemma":[0.0031383105,0.000050319344,0.000019483301,0.00017018648,0.00023532525,0.0028651173,0.00057856133,0.00010910766,0.0000013195905],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021358523,0.000045855548,0.9817805,9.850493e-7,0.000008296144,7.286274e-7,0.0015359594,0.0002706882,0.000074693446,0.007864034,0.000081716265,0.008315145],"study_design_scores_gemma":[0.00023808789,0.000011643799,0.9953709,0.000047418165,0.0000047121657,0.000004299062,0.0015006594,0.0010508798,0.00000813356,0.0010148596,0.00068717106,0.00006118293],"about_ca_topic_score_codex":0.012483829,"about_ca_topic_score_gemma":0.07778347,"teacher_disagreement_score":0.06529964,"about_ca_system_score_codex":0.00025091402,"about_ca_system_score_gemma":0.00056301116,"threshold_uncertainty_score":0.9940921},"labels":[],"label_agreement":null},{"id":"W2605448987","doi":"10.23889/ijpds.v1i1.34","title":"Using linked health survey and Census data to understand transitions to instutional care among Canadian seniors","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Census; American Community Survey; Marital status; Gerontology; Demography; Institutionalisation; Health care; Retirement community; Survey data collection; Long-term care; Community health; Geography; Medicine; Public health; Population; Sociology; Economic growth; Statistics; Nursing","score_opus":0.44555092654699013,"score_gpt":0.536911903484766,"score_spread":0.0913609769377759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605448987","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.888968,0.000064449305,0.010072427,0.067945465,0.006125282,0.00075123494,0.025803046,0.000017658318,0.00025244613],"genre_scores_gemma":[0.99031705,0.000036935333,0.0060257,0.0019252729,0.00042558383,0.0000010803723,0.0012241569,0.000005996024,0.000038220158],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99796927,0.000085249114,0.00031265934,0.00037892544,0.0008152334,0.00043867328],"domain_scores_gemma":[0.99755514,0.00008841317,0.00018177048,0.0005264675,0.0006020823,0.0010461275],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0034676327,0.00007927902,0.00011775691,0.0003168088,0.0064560534,0.001519215,0.0025660978,0.000039344017,0.000016177748],"category_scores_gemma":[0.0026945742,0.00008094565,0.000016186055,0.00017335903,0.00028082466,0.0028383876,0.0003351027,0.00011333628,0.0000015001397],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050796414,0.000022737275,0.9372087,0.000017937651,0.000027538465,0.0000087219905,0.010712299,0.0010981013,0.0000065567756,0.028822195,0.0075602024,0.014464216],"study_design_scores_gemma":[0.00017766556,0.000012545991,0.97566444,0.0000687025,0.0000034391935,0.000006544909,0.0039197067,0.0025540425,1.5977149e-7,0.00022877118,0.017258808,0.00010518708],"about_ca_topic_score_codex":0.75920916,"about_ca_topic_score_gemma":0.960802,"teacher_disagreement_score":0.20159286,"about_ca_system_score_codex":0.0010151152,"about_ca_system_score_gemma":0.0028389872,"threshold_uncertainty_score":0.9995173},"labels":[],"label_agreement":null},{"id":"W2605461181","doi":"10.23889/ijpds.v1i1.321","title":"Trends in prevalence, incidence, health system use and cost by persons with dementia in Ontario from 2004 and 2013: a population-based study","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Dementia; Incidence (geometry); Medicine; Gerontology; Population; Demography; Cohort; Health care; Comorbidity; Cohort study; Environmental health; Psychiatry; Disease","score_opus":0.10847388320375015,"score_gpt":0.44467987647806106,"score_spread":0.3362059932743109,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605461181","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959996,0.00012943451,0.00043585442,0.0012816619,0.0009971394,0.0005773031,0.00055627886,0.000009428211,0.000013351418],"genre_scores_gemma":[0.99800366,0.0000144754895,0.0011785569,0.00006282187,0.000069182155,0.000025970141,0.00045360829,0.0000074510695,0.00018427837],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99805814,0.00012173125,0.0005252706,0.00042103624,0.00060372974,0.00027008756],"domain_scores_gemma":[0.9984596,0.00016722057,0.00065777893,0.00037668258,0.0001970491,0.00014171479],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016282774,0.00011292364,0.00019494463,0.0005509939,0.0012700775,0.00042397922,0.0006960315,0.000042373078,0.000032106753],"category_scores_gemma":[0.00022554681,0.000095182,0.000012938685,0.00015057296,0.00006474133,0.0026197548,0.00017051806,0.00028491946,7.0415325e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012267925,0.0000585048,0.9956266,0.000011522636,0.0000101933165,0.000004065732,0.0011209972,0.00007195865,0.000003230943,0.00003621089,0.0012133524,0.0017206471],"study_design_scores_gemma":[0.0018967051,0.00009270876,0.99105823,0.0005045792,0.00001820292,0.000005457273,0.0011300162,0.0047101653,1.5001636e-7,0.00002976052,0.0004566582,0.00009735534],"about_ca_topic_score_codex":0.54651666,"about_ca_topic_score_gemma":0.8089178,"teacher_disagreement_score":0.26240122,"about_ca_system_score_codex":0.0008671277,"about_ca_system_score_gemma":0.00050083763,"threshold_uncertainty_score":0.9768538},"labels":[],"label_agreement":null},{"id":"W2605462390","doi":"10.23889/ijpds.v1i1.357","title":"Balancing Privacy and Utility in Secondary Data Use to Inform Policy","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"PolicyWise for Children & Families","funders":"","keywords":"Safeguarding; Data sharing; Data governance; General partnership; Information governance; Information privacy; Data access; Data Protection Act 1998; Business; Corporate governance; Repurposing; Data collection; Privacy policy; Information sharing; Data security; Consistency (knowledge bases); Internet privacy; Computer science; Computer security; Information system; Data quality; Political science; Management information systems; Engineering; Marketing; World Wide Web; Law; Sociology","score_opus":0.7165778147701756,"score_gpt":0.6718581571517968,"score_spread":0.044719657618378816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605462390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9507347,0.000017179742,0.003496439,0.04207258,0.0012452329,0.00042439532,0.000995625,0.000011620273,0.0010022478],"genre_scores_gemma":[0.9827184,0.00009967519,0.015189149,0.0009286408,0.00042001996,0.000001840217,0.00029220572,0.0000057735174,0.0003442849],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973924,0.00001508973,0.00048454813,0.000445779,0.0014251415,0.0002370276],"domain_scores_gemma":[0.9955776,0.0009761317,0.00024925533,0.0020068598,0.0008695825,0.00032062325],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.008640992,0.000069841335,0.00013042653,0.00041648277,0.00056236424,0.0011274643,0.0041618855,0.00006362117,0.00003478644],"category_scores_gemma":[0.12348712,0.000060078593,0.000016345712,0.00016412421,0.00029327857,0.0063011004,0.004478262,0.0006768214,0.0000058981086],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025225224,0.00005719915,0.82905114,0.000026384992,0.000016632237,0.0000216076,0.00016736302,0.0000061096794,0.0003341689,0.011255962,0.0010060497,0.15780516],"study_design_scores_gemma":[0.0006785004,0.000041393832,0.95756644,0.0001907854,0.0000036961387,0.00008427132,0.000025669662,0.01746371,0.000023275381,0.00940671,0.014456379,0.00005917992],"about_ca_topic_score_codex":0.001794131,"about_ca_topic_score_gemma":0.0016248818,"teacher_disagreement_score":0.15774599,"about_ca_system_score_codex":0.0001895116,"about_ca_system_score_gemma":0.0012639817,"threshold_uncertainty_score":0.99990946},"labels":[],"label_agreement":null},{"id":"W2605512437","doi":"10.23889/ijpds.v1i1.384","title":"An International Cross-cohort Harmonization and Data Integration Initiative towards Achieving Statistical Power and Meaningful Results","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Partnership Against Cancer","funders":"","keywords":"Harmonization; Metadata; Data science; Computer science; Medicine; Information retrieval; World Wide Web","score_opus":0.1064970619000125,"score_gpt":0.4526248381197615,"score_spread":0.346127776219749,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605512437","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7980913,0.000008869096,0.19343776,0.0019573963,0.0016687709,0.00040519473,0.002895035,0.000025181313,0.0015104793],"genre_scores_gemma":[0.96752614,0.00014544741,0.029356383,0.00030591016,0.00023264169,0.000005812243,0.002381456,0.000015214756,0.000030971056],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99671996,0.00007952088,0.00056035194,0.0011355655,0.0012285219,0.00027605586],"domain_scores_gemma":[0.9976496,0.00013754859,0.0006592614,0.0011145525,0.00018291747,0.00025612614],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0046212375,0.00016771468,0.00013593178,0.00015219391,0.0015514478,0.0024833817,0.003237992,0.000059998212,0.00014677005],"category_scores_gemma":[0.0074494546,0.00015813047,0.000013037882,0.00007516854,0.0008226893,0.017336946,0.0022268556,0.00025903955,0.000011666974],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017644085,0.00007726991,0.85008264,0.0000025137588,0.00003268111,0.000013569917,0.00052713905,0.00025941926,0.002249058,0.0016491702,0.00023751128,0.1446926],"study_design_scores_gemma":[0.00059027685,0.00005543505,0.8545998,0.000035299698,0.000014133405,0.00006864208,0.0000863798,0.14136826,0.00010757672,0.001036132,0.0018812765,0.00015681722],"about_ca_topic_score_codex":0.00048590693,"about_ca_topic_score_gemma":0.00017189838,"teacher_disagreement_score":0.16943485,"about_ca_system_score_codex":0.0003228687,"about_ca_system_score_gemma":0.00007593234,"threshold_uncertainty_score":0.9997484},"labels":[],"label_agreement":null},{"id":"W2605521454","doi":"10.23889/ijpds.v1i1.337","title":"Statin therapy and mortality among new long-term care residents in Ontario, Canada: the contribution of clinical assessment data to a population-based cohort study","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Propensity score matching; Statin; Cohort; Population; Observational study; Retrospective cohort study; Cohort study; Emergency medicine; Activities of daily living; Life expectancy; Proportional hazards model; Hazard ratio; Physical therapy; Internal medicine; Confidence interval; Environmental health","score_opus":0.2571162813814204,"score_gpt":0.569999387047858,"score_spread":0.3128831056664376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605521454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99273527,0.00001827706,0.0008457519,0.0009985733,0.003610016,0.0013666161,0.00040907224,0.0000039497163,0.000012453987],"genre_scores_gemma":[0.9975091,0.000010086396,0.0004254671,0.000094473085,0.00023990209,0.000014182919,0.0016583008,0.0000054981138,0.000042966294],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99695975,0.00022553356,0.001000079,0.0004245543,0.0011783644,0.00021170141],"domain_scores_gemma":[0.9964996,0.00035933597,0.0010637555,0.0011580681,0.00076744973,0.00015176396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005046302,0.00009515687,0.0002426958,0.0001259536,0.0011510188,0.00019951536,0.0023343442,0.00004239874,0.00004179398],"category_scores_gemma":[0.0021591198,0.00007059513,0.000022142702,0.000092049915,0.00007136332,0.0011609951,0.0005451687,0.00033470697,2.4615753e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011426375,0.000047684316,0.99548715,0.0000029846028,0.0000278586,0.000003498403,0.00030748185,0.00007477182,0.0000020941275,0.00004563822,0.0008415615,0.0030450341],"study_design_scores_gemma":[0.0015049273,0.00006352501,0.9964494,0.000107586515,0.000025225374,7.728694e-7,0.00047208427,0.00113461,5.537496e-7,0.00007457025,0.00009427791,0.00007244452],"about_ca_topic_score_codex":0.98125356,"about_ca_topic_score_gemma":0.99806035,"teacher_disagreement_score":0.01680679,"about_ca_system_score_codex":0.00079377927,"about_ca_system_score_gemma":0.004468249,"threshold_uncertainty_score":0.8852822},"labels":[],"label_agreement":null},{"id":"W2605548066","doi":"10.23889/ijpds.v1i1.325","title":"Answering questions posed by health system stakeholders using linked administrative health data at the Institute for Clinical Evaluative Sciences (ICES)","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Health care; Public relations; Business; Government (linguistics); Adjudication; Knowledge management; Political science; Computer science","score_opus":0.9143372743156832,"score_gpt":0.7212097133657027,"score_spread":0.19312756094998051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605548066","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33925474,0.00049188244,0.40560964,0.21702428,0.015066072,0.0048994604,0.017503459,0.000071224575,0.000079241014],"genre_scores_gemma":[0.9197589,0.00018941402,0.07176632,0.002200978,0.0012263441,0.000016339265,0.0047723795,0.000015268342,0.000054032647],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9951349,0.0002261972,0.0019358211,0.00079975784,0.0015498117,0.00035352053],"domain_scores_gemma":[0.99242353,0.0011630467,0.0035147124,0.0013277417,0.0012571439,0.00031382986],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.026325392,0.00015180594,0.00031564748,0.0001535858,0.00509364,0.00097531185,0.0033094583,0.000045132805,0.000011859791],"category_scores_gemma":[0.024956249,0.000112164715,0.00008005294,0.0001695692,0.0010382083,0.00591138,0.0009159055,0.00029161607,0.0000028292106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005056928,0.0016868745,0.25080913,0.0004724512,0.001341434,0.000028420807,0.002104373,0.0076070675,0.002498063,0.021648346,0.19217041,0.5145765],"study_design_scores_gemma":[0.0050444724,0.0012020242,0.10500405,0.0008587361,0.00017783866,0.00043312606,0.0025138285,0.8383167,0.00002231298,0.0004942289,0.045650132,0.00028259883],"about_ca_topic_score_codex":0.0027515779,"about_ca_topic_score_gemma":0.002993213,"teacher_disagreement_score":0.8307096,"about_ca_system_score_codex":0.0009696342,"about_ca_system_score_gemma":0.0043440633,"threshold_uncertainty_score":0.9962016},"labels":[],"label_agreement":null},{"id":"W2605572910","doi":"10.23889/ijpds.v1i1.257","title":"IMECCHI-DATANETWORK: empowering knowledge generation through international data network","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; Alberta Children's Hospital; University of Calgary","funders":"","keywords":"Raw data; Computer science; Identifier; Data science; Table (database); Software; Data mining; Matching (statistics); Protocol (science); Observational study; Medicine","score_opus":0.20714538692188547,"score_gpt":0.4843355718825411,"score_spread":0.2771901849606556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605572910","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14940827,0.0021214741,0.7637684,0.007985917,0.0697295,0.00054470473,0.0025439924,0.00008062041,0.0038171678],"genre_scores_gemma":[0.9038889,0.0005983111,0.07293321,0.0002679934,0.011206172,0.0000060239727,0.010525972,0.000018345256,0.00055510976],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982041,0.000027402777,0.00037043946,0.0006432149,0.00046941283,0.00028544565],"domain_scores_gemma":[0.99743384,0.000026987324,0.0004241377,0.0016110691,0.00040893897,0.00009500418],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0017044719,0.00012997202,0.00010974133,0.000060665345,0.0011340107,0.0010130721,0.007780159,0.00008993205,0.00002838793],"category_scores_gemma":[0.0022167407,0.00011685354,0.00003909514,0.000046933652,0.00030790927,0.00038073247,0.003205945,0.00013743188,0.000008472043],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000310031,0.00020993873,0.045591567,0.000009388581,0.00039888886,0.000017107626,0.0001500836,0.0022205361,0.032078367,0.0047970847,0.27569225,0.6385248],"study_design_scores_gemma":[0.00065321964,0.00006415705,0.018308748,0.00004845313,0.000018807705,0.00014287168,0.000023506529,0.11674864,0.0004927762,0.0008927191,0.8623721,0.00023401262],"about_ca_topic_score_codex":0.00007228563,"about_ca_topic_score_gemma":0.00023440043,"teacher_disagreement_score":0.7544806,"about_ca_system_score_codex":0.000045287245,"about_ca_system_score_gemma":0.0001979574,"threshold_uncertainty_score":0.9975882},"labels":[],"label_agreement":null},{"id":"W2605606480","doi":"10.23889/ijpds.v1i1.144","title":"The Nascent Pan-Canadian Real-world Health Data Network (PRHDN)","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Legislature; Data sharing; Census; Data science; Knowledge translation; Plan (archaeology); Population; Computer science; Business; Knowledge management; Geography; Medicine; Environmental health","score_opus":0.2889966618631031,"score_gpt":0.572883782227088,"score_spread":0.28388712036398495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605606480","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009243981,0.0010154834,0.004825566,0.84218425,0.10507504,0.003099069,0.0071767373,0.00012260412,0.0272573],"genre_scores_gemma":[0.8832307,0.00749318,0.01365041,0.059123226,0.017735919,0.00006649022,0.0066329963,0.00007051204,0.011996554],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964237,0.0001668397,0.0009242383,0.00049571664,0.0010402625,0.0009492397],"domain_scores_gemma":[0.99409944,0.0005527238,0.0013136822,0.002779443,0.0007081172,0.0005465896],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.010238654,0.00012836316,0.0001964358,0.00021732239,0.018978,0.0007718622,0.011039795,0.000051722996,0.000109046],"category_scores_gemma":[0.0026043253,0.00009141565,0.00003881845,0.00016101371,0.00021690915,0.0035990013,0.002140187,0.00057481375,0.00007601667],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004984157,0.000010505255,0.25863275,0.000011504575,0.00002535153,0.0000042170245,0.00009380672,0.000018873578,0.0000012870283,0.03342416,0.609757,0.09797072],"study_design_scores_gemma":[0.00024096268,0.000011836157,0.42818433,0.000058843158,0.000004220537,0.000005101488,0.000053193828,0.0024557998,8.430302e-8,0.0027314236,0.56618977,0.0000644655],"about_ca_topic_score_codex":0.17341517,"about_ca_topic_score_gemma":0.73663884,"teacher_disagreement_score":0.8739867,"about_ca_system_score_codex":0.001823898,"about_ca_system_score_gemma":0.009096159,"threshold_uncertainty_score":0.99652135},"labels":[],"label_agreement":null},{"id":"W2605607505","doi":"10.23889/ijpds.v1i1.32","title":"Using Canadian data linkage to investigate the socioeconomic patterning of hospital burden for childbirth","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada; McGill University","funders":"","keywords":"Childbirth; Medicine; Socioeconomic status; Vaginal delivery; Record linkage; Demography; Household income; Population; Health care; Medical record; Pregnancy; Environmental health; Emergency medicine; Obstetrics; Geography","score_opus":0.13949679253673875,"score_gpt":0.4349027863908649,"score_spread":0.29540599385412614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605607505","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9675503,0.000016255504,0.0022284717,0.02507863,0.0022441798,0.00038979197,0.0024366684,0.000004077394,0.00005165476],"genre_scores_gemma":[0.99039376,0.000012933317,0.006759577,0.0012179536,0.0011627664,0.00000196585,0.00040477683,0.000007846063,0.000038442126],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99881697,0.000008523368,0.0003261814,0.00027717234,0.00034196646,0.0002291756],"domain_scores_gemma":[0.9981151,0.000030232066,0.00039645223,0.00082858984,0.00034885757,0.00028075054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011667318,0.000075645905,0.00012339948,0.00013555745,0.0009656732,0.0003486585,0.0031938127,0.0000252357,0.000016329152],"category_scores_gemma":[0.0008956215,0.000055388187,0.000032253887,0.000029335597,0.00013922511,0.0012581088,0.00053238176,0.0001088661,0.0000046826813],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013723846,0.000043066862,0.96990573,0.000050739585,0.00013076465,0.000012307605,0.00063940906,0.001100444,0.0013340802,0.0039491733,0.004812091,0.017884975],"study_design_scores_gemma":[0.0008175088,0.00012214476,0.9022721,0.00025788872,0.00004277964,0.00011671809,0.000111628564,0.078713566,0.000095709875,0.0015751391,0.01575195,0.00012289],"about_ca_topic_score_codex":0.039007604,"about_ca_topic_score_gemma":0.0061653843,"teacher_disagreement_score":0.07761312,"about_ca_system_score_codex":0.00019660618,"about_ca_system_score_gemma":0.0006001206,"threshold_uncertainty_score":0.9673917},"labels":[],"label_agreement":null},{"id":"W2605612746","doi":"10.23889/ijpds.v1i1.391","title":"Furthering the idea of proportionate governance in British Columbia","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Data science; Process (computing); Risk analysis (engineering); Scalability; Audit; Work (physics); Transparency (behavior); Corporate governance; Presentation (obstetrics); Knowledge management; Business; Computer security; Engineering; Accounting","score_opus":0.44421006839600313,"score_gpt":0.5989289121946555,"score_spread":0.15471884379865236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605612746","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98765343,0.00005186312,0.00078355666,0.008994902,0.0014445714,0.00029042977,0.00018029648,0.0000048456764,0.0005961072],"genre_scores_gemma":[0.9956624,0.0002900253,0.0027641328,0.00011309949,0.00022863365,0.0000047706426,0.00002594082,0.000005466866,0.000905524],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973662,0.000015317073,0.00048794557,0.00023655844,0.0017421938,0.00015179314],"domain_scores_gemma":[0.9971268,0.0004206777,0.0005530153,0.0006533576,0.0011783118,0.000067793524],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0065763085,0.00003385999,0.00010308062,0.000038731516,0.00048612716,0.0008657526,0.0026812153,0.00004387565,0.00008828196],"category_scores_gemma":[0.033138163,0.00003507088,0.00003880802,0.00008773815,0.00056632725,0.0012854141,0.0005942029,0.0004662786,0.0000018350393],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046565972,0.00006416279,0.9382057,0.000017200991,0.000015175545,0.000026132915,0.000027477872,0.000050111452,0.00050284603,0.0052675754,0.00035556147,0.055421494],"study_design_scores_gemma":[0.0005213586,0.000033788172,0.9630285,0.00034429968,0.0000042033375,0.00012457135,0.000025866737,0.0071857343,0.000030738716,0.027444558,0.0012199302,0.000036470763],"about_ca_topic_score_codex":0.012257626,"about_ca_topic_score_gemma":0.07072165,"teacher_disagreement_score":0.058464024,"about_ca_system_score_codex":0.00013471892,"about_ca_system_score_gemma":0.000488977,"threshold_uncertainty_score":0.99431986},"labels":[],"label_agreement":null},{"id":"W2605680824","doi":"10.23889/ijpds.v1i1.36","title":"Describing the Linkages of the Citizenship and Immigration Canada Permanent Resident Data and Vital Statistics—Death Registry to Ontario’s Administrative Health Database","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ottawa Hospital; Canadian Institute for Health Information; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Record linkage; Linkage (software); Database; Immigration; Demography; Geography; Medicine; Computer science; Environmental health; Population; Sociology; Biology; Genetics","score_opus":0.34664563996021425,"score_gpt":0.4069664830768868,"score_spread":0.06032084311667257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605680824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7348095,0.0003905317,0.040265743,0.17593376,0.0037472846,0.0010194812,0.04339728,0.0000058873243,0.00043053052],"genre_scores_gemma":[0.9959013,0.00009807642,0.0025677227,0.00077714154,0.00010797086,0.0000030896615,0.000348925,0.0000034924371,0.00019232239],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9989091,0.000019324421,0.00043083038,0.0002998525,0.00019835522,0.00014253831],"domain_scores_gemma":[0.99812573,0.000072950796,0.00070867577,0.000867522,0.000104199964,0.00012089847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019978385,0.000064533924,0.00010252915,0.00006681249,0.0010087885,0.0005030462,0.0018523564,0.0000117004765,0.000007317004],"category_scores_gemma":[0.001717525,0.00004925308,0.0000083449195,0.000036294183,0.00010923434,0.00078824995,0.0010048258,0.00011353656,3.325893e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004190215,0.000027411495,0.40499106,0.0000491693,0.00007802795,0.000008330997,0.0022151866,0.00009656515,0.00002691628,0.54912907,0.03384875,0.009487601],"study_design_scores_gemma":[0.00023276701,0.00004083521,0.9667562,0.00010555328,0.0000060573284,0.00003360869,0.00037955953,0.008389833,0.000013214186,0.008056823,0.015887555,0.000097993245],"about_ca_topic_score_codex":0.78267556,"about_ca_topic_score_gemma":0.86763024,"teacher_disagreement_score":0.56176513,"about_ca_system_score_codex":0.0002807373,"about_ca_system_score_gemma":0.00071872154,"threshold_uncertainty_score":0.77588874},"labels":[],"label_agreement":null},{"id":"W2605681521","doi":"10.23889/ijpds.v1i1.143","title":"No Strings Attached: Evaluating an Unconditional Prenatal Income Supplement Using Linked Administrative Data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Prenatal Substance Exposure Effects","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Birth certificate; Medicine; Breastfeeding; Population; Low birth weight; Demography; Birth weight; Socioeconomic status; Disadvantaged; Prenatal care; Environmental health; Pregnancy; Pediatrics","score_opus":0.31179793008220624,"score_gpt":0.5367692809376124,"score_spread":0.2249713508554062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605681521","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97413266,0.000030424024,0.012976461,0.00079438847,0.004209264,0.0007310732,0.0069790334,0.00003483404,0.00011188315],"genre_scores_gemma":[0.9040232,0.000003185221,0.0808844,0.000081530416,0.0016210128,0.000007717845,0.013293008,0.000016273862,0.00006969478],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99607617,0.000054396944,0.0006117132,0.0007569354,0.0021632016,0.0003375595],"domain_scores_gemma":[0.9955118,0.000130755,0.0009325884,0.0017937568,0.0013217939,0.0003093184],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0037668163,0.00018287003,0.0002134753,0.0002455682,0.001290461,0.0010973683,0.0047024004,0.000058184993,0.00017503182],"category_scores_gemma":[0.005704199,0.00016621497,0.000046054593,0.00010283546,0.00029509756,0.010862152,0.0015997154,0.00030658368,0.000011767044],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031900029,0.0009694592,0.8687528,0.00016219531,0.00076390593,0.0003752064,0.0005981022,0.0016526796,0.06875191,0.008372191,0.0028856343,0.043525938],"study_design_scores_gemma":[0.0029636652,0.0004962654,0.5841485,0.0004512578,0.00009045945,0.0006763898,0.00005754781,0.40752432,0.0012220421,0.0010146328,0.0010855279,0.0002693701],"about_ca_topic_score_codex":0.00024733596,"about_ca_topic_score_gemma":0.00015582252,"teacher_disagreement_score":0.40587163,"about_ca_system_score_codex":0.000464703,"about_ca_system_score_gemma":0.00090634363,"threshold_uncertainty_score":0.99993956},"labels":[],"label_agreement":null},{"id":"W2605682099","doi":"10.23889/ijpds.v1i1.186","title":"Small area variation in the utilization of common medical tests and consultations in Ontario, Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare cost, quality, practices","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Queen's University","funders":"","keywords":"Overdiagnosis; Medicine; Population; Health care; Demography; Test (biology); Family medicine; Environmental health; Pathology","score_opus":0.7680049185607403,"score_gpt":0.6030306465228915,"score_spread":0.16497427203784876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605682099","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9771597,0.00001757688,0.0011686846,0.019080695,0.001642542,0.00043815208,0.00014625129,0.0000032283872,0.00034320963],"genre_scores_gemma":[0.9977499,0.000037579834,0.0007778637,0.0011131732,0.00008392899,0.000016425925,0.00018235607,0.00000384523,0.000034877467],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972767,0.0003945455,0.0008229923,0.00022127341,0.0010830868,0.00020140043],"domain_scores_gemma":[0.9959167,0.0018063365,0.0010331235,0.0004348411,0.0007090977,0.000099855046],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008788932,0.00006851762,0.00012937265,0.00020592859,0.0010107785,0.00012090786,0.0017297578,0.00006894073,0.00007170666],"category_scores_gemma":[0.021563191,0.000054235625,0.000009234512,0.00014065664,0.00015116364,0.0017853498,0.00027032738,0.00053188764,6.326192e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033819855,0.000045217275,0.9855385,0.000013263232,0.0000040298282,0.0000058471155,0.0017529968,0.00003962249,0.000019491004,0.008588773,0.00024277993,0.0037156532],"study_design_scores_gemma":[0.0006058998,0.000013806385,0.9805228,0.00020478999,0.0000044230237,0.000016224116,0.0006590899,0.0129920365,0.000001125677,0.0024991224,0.0024303196,0.0000503725],"about_ca_topic_score_codex":0.9584666,"about_ca_topic_score_gemma":0.9987312,"teacher_disagreement_score":0.04026458,"about_ca_system_score_codex":0.00061814004,"about_ca_system_score_gemma":0.004760885,"threshold_uncertainty_score":0.9866786},"labels":[],"label_agreement":null},{"id":"W2605683313","doi":"10.23889/ijpds.v1i1.305","title":"Patient Engagement as a Component of a Learning Healthcare System: A case study using small area rate variation research in Nova Scotia, Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick; University of Prince Edward Island; Nova Scotia Department of Health and Wellness; Nova Scotia Health Authority; Dalhousie University","funders":"","keywords":"Proxy (statistics); Nova scotia; Health care; Patient experience; Medicine; Psychology; Business; Family medicine; Geography; Computer science; Political science","score_opus":0.5308199856062593,"score_gpt":0.5827591844494155,"score_spread":0.05193919884315623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605683313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99033535,0.000025379932,0.0007376433,0.0030330068,0.004251392,0.0013246158,0.00014922781,0.000007926624,0.00013546777],"genre_scores_gemma":[0.9984039,0.000005542596,0.0010065635,0.00025883198,0.0001991396,0.00001688505,0.00007533796,0.000010271962,0.000023526925],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9955323,0.0010873276,0.0011241791,0.0003951815,0.0013903646,0.00047067576],"domain_scores_gemma":[0.9952748,0.00060766446,0.0012775674,0.0006195685,0.0020372649,0.00018312584],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.012571776,0.00010776337,0.0002426681,0.0005959365,0.0034442502,0.00016070309,0.0013157967,0.000046904595,0.000025002195],"category_scores_gemma":[0.002182254,0.00009856357,0.000024832987,0.00023386418,0.00006692676,0.001056454,0.0010405,0.0008174894,0.0000027163803],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00024980228,0.00016713375,0.9839459,0.00024065842,0.000040086816,0.00082753255,0.0055264332,0.0020161911,0.00022838962,0.0017689555,0.00034031304,0.004648568],"study_design_scores_gemma":[0.0032002162,0.00047068737,0.84306306,0.0014944073,0.00003106527,0.00060272403,0.05785657,0.09119181,0.000011206477,0.00035113163,0.0014453306,0.00028179557],"about_ca_topic_score_codex":0.95383745,"about_ca_topic_score_gemma":0.90425134,"teacher_disagreement_score":0.14088288,"about_ca_system_score_codex":0.0044682184,"about_ca_system_score_gemma":0.0071570673,"threshold_uncertainty_score":0.99935347},"labels":[],"label_agreement":null},{"id":"W2605684939","doi":"10.23889/ijpds.v1i1.38","title":"Canadian data sources on ethnic classifications: Contemporary and historical developments in heterogeneity","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Ethnic group; Census; Population; Geography; Medicine; Political science; Environmental health; Law","score_opus":0.5551561339614477,"score_gpt":0.5426009392500483,"score_spread":0.012555194711399431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605684939","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9651576,0.0002854167,0.00035831283,0.021076653,0.008940466,0.0007510431,0.0010931859,0.00001372675,0.0023235402],"genre_scores_gemma":[0.9972446,0.0001406106,0.0009191506,0.0006939568,0.0002846953,0.000016251064,0.00043075136,0.0000058586747,0.00026410562],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99840266,0.000060155966,0.00043541164,0.00037507672,0.00033208128,0.00039462888],"domain_scores_gemma":[0.9982098,0.00014511567,0.000420954,0.00072428206,0.0003311719,0.0001686794],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0029072128,0.00007534187,0.000119860786,0.00029753955,0.006639655,0.000119194534,0.002797138,0.000065130065,0.00001569445],"category_scores_gemma":[0.0023295712,0.000066549044,0.00000984386,0.00006162969,0.00008953991,0.0014605853,0.00104589,0.00027374242,0.000015800897],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034359193,0.000025692536,0.9868486,0.0000047376257,0.000015699656,0.00000676134,0.0009310148,0.00000647474,0.000011976376,0.001432311,0.00542908,0.005253275],"study_design_scores_gemma":[0.00038386357,0.000019227024,0.9072667,0.000042285006,0.0000025323218,0.0000074762665,0.0005079953,0.0014458,7.792779e-7,0.0003030311,0.08994577,0.00007456292],"about_ca_topic_score_codex":0.1476139,"about_ca_topic_score_gemma":0.73734194,"teacher_disagreement_score":0.58972806,"about_ca_system_score_codex":0.0019855862,"about_ca_system_score_gemma":0.0015679109,"threshold_uncertainty_score":0.9946536},"labels":[],"label_agreement":null},{"id":"W2605708979","doi":"10.23889/ijpds.v1i1.403","title":"Thoughts and musings from the new International Population Data Linkage Network (IPDLN) Co-directors","year":2017,"lang":"en","type":"editorial","venue":"International Journal for Population Data Science","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Population; Attendance; Operations research; Medicine; Computer science; Engineering; Political science; Law","score_opus":0.07369660455808226,"score_gpt":0.43439949610203943,"score_spread":0.3607028915439572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605708979","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005572296,0.0014196147,0.00429488,0.0036359867,0.97478616,0.0007981502,0.009260287,0.00006256663,0.00017005058],"genre_scores_gemma":[0.015246276,0.003297718,0.00598188,0.00028701633,0.8790145,0.0000054122634,0.095431946,0.000058728947,0.0006765448],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.993406,0.000095138355,0.0009567404,0.0012202851,0.003848019,0.00047380698],"domain_scores_gemma":[0.9936859,0.000897691,0.0013894747,0.0024927927,0.0010528436,0.00048131877],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0038950024,0.0003710884,0.0005531573,0.00030971202,0.0014374465,0.0018415529,0.00585061,0.00040996217,0.000058778754],"category_scores_gemma":[0.009522244,0.00026589644,0.0001898039,0.00017572823,0.00027347176,0.0032986258,0.0015645436,0.0011576454,0.000011198363],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026941355,0.000025475803,0.020280246,0.000014095596,0.0003381828,0.00002250284,0.00008059939,0.00006481034,0.0000095007035,0.000033787997,0.94042027,0.038441114],"study_design_scores_gemma":[0.0013827004,0.000032882817,0.10594384,0.0005451254,0.00028592904,0.00008862194,0.000023758197,0.006120906,0.0000022598576,0.000547418,0.8847717,0.0002548296],"about_ca_topic_score_codex":0.006939402,"about_ca_topic_score_gemma":0.0015371395,"teacher_disagreement_score":0.095771685,"about_ca_system_score_codex":0.0004725679,"about_ca_system_score_gemma":0.0015010064,"threshold_uncertainty_score":0.9999793},"labels":[],"label_agreement":null},{"id":"W2605813800","doi":"10.23889/ijpds.v1i1.171","title":"Modelling Diagnostic Validity Estimates from Administrative Health Data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Statistics; Univariate; Bivariate analysis; Confidence interval; Youden's J statistic; Mean squared error; Mathematics; Sensitivity (control systems); Complement (music); Variance (accounting); Regression; Correlation; Regression analysis; Standard error; Econometrics; Multivariate statistics","score_opus":0.7832932054931357,"score_gpt":0.6179929298057897,"score_spread":0.16530027568734607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605813800","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029593306,0.000027869859,0.9625064,0.00207427,0.0014638181,0.00027002665,0.00390987,0.00007081097,0.00008362346],"genre_scores_gemma":[0.5981053,0.00007848651,0.40030065,0.000059195754,0.00032285674,0.0000051705974,0.0011025469,0.000010128926,0.000015632444],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977028,0.000031978925,0.00055529183,0.000548188,0.0009019346,0.00025981487],"domain_scores_gemma":[0.9945029,0.0015811666,0.0011776845,0.0020281863,0.00054236985,0.0001676782],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0023893092,0.00014158523,0.0001992809,0.00011888701,0.0013008631,0.001231976,0.0074309236,0.00003699463,0.0000352872],"category_scores_gemma":[0.021910366,0.00012656435,0.000028105002,0.00005268513,0.0002537233,0.007617014,0.0015528578,0.00020619346,0.0000047221206],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003532912,0.0010457603,0.115113236,0.00009431956,0.00036188125,0.00011428579,0.0013028315,0.012339638,0.0010337587,0.685202,0.04415702,0.13888197],"study_design_scores_gemma":[0.00018124729,0.00004511238,0.0038997438,0.00016143266,0.00001417534,0.000025525957,0.000034369878,0.41493323,0.0002261905,0.57942027,0.000923451,0.00013526203],"about_ca_topic_score_codex":0.00079240167,"about_ca_topic_score_gemma":0.00022570406,"teacher_disagreement_score":0.568512,"about_ca_system_score_codex":0.00019729321,"about_ca_system_score_gemma":0.00036811281,"threshold_uncertainty_score":0.9999993},"labels":[],"label_agreement":null},{"id":"W2605838351","doi":"10.23889/ijpds.v1i1.74","title":"Does quality of primary care vary across delivery models?","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health","funders":"","keywords":"Referral; Primary care; Medicine; Ambulatory care; Family medicine; Service delivery framework; Service (business); Population; Quality (philosophy); Health care; Environmental health; Business","score_opus":0.33195761060509915,"score_gpt":0.5851423606806224,"score_spread":0.25318475007552327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605838351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95048344,0.00020989034,0.009007035,0.0070406613,0.020542217,0.00069020275,0.0056867697,0.00004343794,0.006296351],"genre_scores_gemma":[0.9901263,0.00021586126,0.0056507504,0.002004741,0.00082097173,0.0000109268385,0.0007124141,0.000010233461,0.0004477647],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997199,0.0000949531,0.00091211166,0.0003382028,0.00108024,0.0003755049],"domain_scores_gemma":[0.9951809,0.00030748267,0.0014118749,0.0010108955,0.001940397,0.00014844869],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0032526217,0.00010250717,0.00024648407,0.00013091469,0.003474247,0.00016125101,0.0037476516,0.00008039079,0.00005067732],"category_scores_gemma":[0.0010787861,0.000068092,0.000074132695,0.000059258866,0.00023668986,0.0054699634,0.0014711347,0.00032177722,0.000007879904],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054683816,0.00006975543,0.88383317,0.0004261805,0.000056798886,0.0000058248747,0.0029187533,0.00019415445,0.0009849011,0.013897122,0.006339774,0.09072674],"study_design_scores_gemma":[0.0010745621,0.000025239155,0.9739738,0.00015062164,0.000010133372,0.0000037861514,0.001037924,0.0014620598,0.000028382168,0.0086467825,0.013446852,0.00013986965],"about_ca_topic_score_codex":0.0025820653,"about_ca_topic_score_gemma":0.0013140502,"teacher_disagreement_score":0.09058687,"about_ca_system_score_codex":0.0008225532,"about_ca_system_score_gemma":0.001733891,"threshold_uncertainty_score":0.9978231},"labels":[],"label_agreement":null},{"id":"W2605867622","doi":"10.23889/ijpds.v1i1.359","title":"Suicide Prevention through Shared Information","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Harm; Mental health; Biobank; Medicine; Psychology; Protocol (science); Service (business); Medical emergency; Psychiatry; Business; Social psychology; Alternative medicine","score_opus":0.8449930898923401,"score_gpt":0.7662158147211987,"score_spread":0.07877727517114141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605867622","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3386852,0.00002098236,0.49764714,0.09643066,0.04261206,0.003982593,0.0045828307,0.00021514022,0.015823366],"genre_scores_gemma":[0.95033866,0.000055858472,0.039744038,0.0067374064,0.0014181812,0.00007684726,0.00081787887,0.000011671702,0.0007994356],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9965011,0.000119470125,0.0011112079,0.00029382747,0.0014655899,0.00050883234],"domain_scores_gemma":[0.99469954,0.00034553857,0.0019910443,0.00095806684,0.0018084616,0.00019735748],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0061418936,0.0001064671,0.0001314455,0.0002976428,0.0062135775,0.00093257456,0.004461579,0.00006192988,0.00041586848],"category_scores_gemma":[0.015664093,0.000096296,0.000041070925,0.00016229716,0.00020278878,0.030428503,0.0008748586,0.00029242184,0.000230104],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004058161,0.000071229144,0.49485743,0.00012449577,0.000077855446,0.0000055754563,0.011282835,0.00025291115,0.0012464352,0.12157312,0.14909047,0.22101182],"study_design_scores_gemma":[0.0017416549,0.000053087548,0.5975761,0.00021886948,0.000011022628,0.000022438227,0.0007450661,0.0070666317,0.00004432258,0.019647466,0.37268978,0.00018360604],"about_ca_topic_score_codex":0.0010548631,"about_ca_topic_score_gemma":0.0004206178,"teacher_disagreement_score":0.61165345,"about_ca_system_score_codex":0.00047832946,"about_ca_system_score_gemma":0.0012309705,"threshold_uncertainty_score":0.9950802},"labels":[],"label_agreement":null},{"id":"W2605887500","doi":"10.23889/ijpds.v1i1.133","title":"CanIMPACT: Understanding complexities, variation, and disparities in the breast cancer care continuum in Five Canadian provinces using administrative data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; Cancer Care Ontario; University Health Network; Dalhousie University; BC Cancer Agency; CancerCare Manitoba","funders":"","keywords":"Medicine; Breast cancer; Family medicine; Health care; Context (archaeology); Census; Cancer; Geography; Environmental health; Population; Economic growth","score_opus":0.5217751545782924,"score_gpt":0.5174592993912585,"score_spread":0.0043158551870339235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605887500","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9697885,0.00031326522,0.0013978463,0.01684898,0.0011753549,0.0005945917,0.0094015915,0.000005490282,0.00047437215],"genre_scores_gemma":[0.9981683,0.000037459315,0.0008324359,0.0003136755,0.0002505167,0.0000033907527,0.00038043075,0.000003641134,0.000010184211],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99870306,0.000023779645,0.00025176292,0.00026448423,0.0005420076,0.00021489181],"domain_scores_gemma":[0.9989262,0.00005702822,0.00023998848,0.0003943947,0.00027428908,0.00010806659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010017727,0.00007849505,0.000114265036,0.00020659255,0.0007781409,0.0009520656,0.0015052868,0.000025834632,0.000013005957],"category_scores_gemma":[0.00060284586,0.000059944203,0.000010374065,0.000097916985,0.00024641404,0.0031071298,0.00021013987,0.00015171223,1.1816928e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009476936,0.000007929102,0.99213606,0.000009713842,0.000013672791,0.000035300778,0.0016910385,0.000085372834,0.000025836256,0.0046168985,0.0003497854,0.0009335971],"study_design_scores_gemma":[0.000497292,0.000021683785,0.9623905,0.0003144532,0.000016501479,0.00033223422,0.006267592,0.028375514,0.0000014764646,0.0015029263,0.00020746911,0.000072389004],"about_ca_topic_score_codex":0.5994976,"about_ca_topic_score_gemma":0.86081666,"teacher_disagreement_score":0.26131907,"about_ca_system_score_codex":0.0012297202,"about_ca_system_score_gemma":0.001655495,"threshold_uncertainty_score":0.918079},"labels":[],"label_agreement":null},{"id":"W2605901610","doi":"10.23889/ijpds.v1i1.329","title":"Supporting Multidisciplinary Analytic Skills: An Innovative Training Platform for Capacity Building","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Multidisciplinary approach; Knowledge management; Population; Population health; Capacity building; Analytics; Medical education; Psychology; Computer science; Medicine; Data science; Political science","score_opus":0.39795306731210217,"score_gpt":0.6238020999699034,"score_spread":0.22584903265780126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605901610","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9397641,0.000003541742,0.042657882,0.006153306,0.009558598,0.00072048354,0.00076157076,0.000032117285,0.0003484368],"genre_scores_gemma":[0.95681316,0.000006183048,0.038586475,0.000592099,0.003029353,0.000058624482,0.00063928805,0.00001641916,0.00025842397],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971604,0.000047183803,0.0009750158,0.00043345673,0.0006513036,0.00073264795],"domain_scores_gemma":[0.99448526,0.0004476312,0.001839122,0.0006863576,0.0022378906,0.00030374216],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.008512018,0.00012919315,0.00019608575,0.0004325221,0.008194283,0.00047750762,0.0027299125,0.00008855222,0.000045021538],"category_scores_gemma":[0.01169103,0.00011478818,0.000042641248,0.0002113992,0.00018996824,0.008291994,0.0004984192,0.0003851474,0.000004145639],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034385393,0.00044515423,0.54512423,0.00022453297,0.00015881858,0.0000043801065,0.059492104,0.00090439146,0.00337364,0.14343527,0.011163051,0.2353306],"study_design_scores_gemma":[0.0016149755,0.00013980186,0.6957932,0.00033916652,0.000019989313,0.00003454825,0.008857161,0.23244488,0.000040130348,0.023398664,0.036997404,0.00032004653],"about_ca_topic_score_codex":0.001274206,"about_ca_topic_score_gemma":0.00046177531,"teacher_disagreement_score":0.23501055,"about_ca_system_score_codex":0.00063008803,"about_ca_system_score_gemma":0.0015768254,"threshold_uncertainty_score":0.9966339},"labels":[],"label_agreement":null},{"id":"W2605936277","doi":"10.23889/ijpds.v1i1.272","title":"Cautionary accounts in the use of health equity measures from linkable administrative data in population health intervention research","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Health equity; Equity (law); Socioeconomic status; Social determinants of health; Population; Population health; Psychology; Actuarial science; Demographic economics; Business; Medicine; Environmental health; Public health; Economics; Political science; Nursing","score_opus":0.9161210031765762,"score_gpt":0.717884752333229,"score_spread":0.19823625084334717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605936277","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89492804,0.0005717606,0.0048764595,0.07489508,0.0076066535,0.0039512278,0.012915551,0.000031192183,0.00022406582],"genre_scores_gemma":[0.98884934,0.0002826358,0.00349755,0.000644055,0.0003967279,0.00003407343,0.0062493156,0.000009903085,0.00003638983],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9926577,0.0017379121,0.001966045,0.00063945464,0.002356972,0.00064187084],"domain_scores_gemma":[0.99356925,0.0011695419,0.0021733772,0.0018677452,0.0010759045,0.0001441565],"candidate_categories":["metaresearch","sts","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.032500107,0.00013349974,0.0003178437,0.0007482575,0.004383983,0.00044274697,0.005824535,0.00011570527,0.000058299316],"category_scores_gemma":[0.010706358,0.00011340761,0.00004248131,0.00042529518,0.0002927524,0.007696332,0.002042848,0.0010848584,0.000009016959],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025386628,0.00035806742,0.94188076,0.00008001466,0.000019502591,0.0000033330884,0.0034026664,0.00036645055,0.000007261966,0.020652855,0.006396849,0.02657838],"study_design_scores_gemma":[0.000913579,0.00009575639,0.9510343,0.0008234173,0.0000037543793,0.0000036284061,0.0017621112,0.021434324,3.9390986e-7,0.015033881,0.008808255,0.000086600216],"about_ca_topic_score_codex":0.15238133,"about_ca_topic_score_gemma":0.11712631,"teacher_disagreement_score":0.09392133,"about_ca_system_score_codex":0.001250008,"about_ca_system_score_gemma":0.0020077878,"threshold_uncertainty_score":0.99955446},"labels":[],"label_agreement":null},{"id":"W2605947039","doi":"10.23889/ijpds.v1i1.386","title":"Novel Tools Supporting Knowledge Translation for Public Health Practice in British Columbia, Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ministry of Health; Public Health Agency of Canada","funders":"","keywords":"Public health informatics; Computer science; Data access; Public health; Context (archaeology); Data quality; Analytics; Health information exchange; Data science; Health informatics; Health care; Knowledge management; Medicine; HRHIS; Health policy; Health information; Business; Service (business); Database; Nursing","score_opus":0.2267762348935681,"score_gpt":0.4628224468803397,"score_spread":0.2360462119867716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605947039","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8375321,0.0009857207,0.08785055,0.053137045,0.013129545,0.0030480819,0.0038056322,0.000036416444,0.00047489564],"genre_scores_gemma":[0.983255,0.00015237798,0.014167963,0.00063486537,0.00061083894,0.000015412266,0.0010393698,0.000011344237,0.00011277694],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99784404,0.000024696948,0.0006078633,0.00033058572,0.0008182596,0.00037453786],"domain_scores_gemma":[0.9973281,0.0002647387,0.0006594299,0.00041065723,0.001024522,0.00031253058],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004857346,0.00006167399,0.00019678843,0.00012251809,0.0011019525,0.0016784933,0.0008520261,0.00003616673,0.000012073275],"category_scores_gemma":[0.0139158275,0.00008293097,0.00007144627,0.000111572655,0.000067258174,0.0037706483,0.00008713725,0.00017320692,4.0464093e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051846622,0.00013438555,0.13192786,0.000050531373,0.000051731895,0.000015004666,0.00017228785,0.00004750807,0.00008351541,0.00008711334,0.003437042,0.8639412],"study_design_scores_gemma":[0.0024020344,0.000057441695,0.7450089,0.00014869864,0.000017825387,0.0009049314,0.00026603622,0.013788341,0.000003598395,0.0000518166,0.2372422,0.000108207954],"about_ca_topic_score_codex":0.72375077,"about_ca_topic_score_gemma":0.96069694,"teacher_disagreement_score":0.86383295,"about_ca_system_score_codex":0.00075165095,"about_ca_system_score_gemma":0.0056578894,"threshold_uncertainty_score":0.9999791},"labels":[],"label_agreement":null},{"id":"W2605947894","doi":"10.23889/ijpds.v1i1.154","title":"Variations in antibiotic use for respiratory tract infections","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Respiratory tract infections; Specialty; Medical prescription; Antibiotics; Cohort; Family medicine; Population; Health care; Emergency medicine; Intensive care medicine; Pediatrics; Internal medicine; Environmental health; Respiratory system; Nursing","score_opus":0.10999032342885187,"score_gpt":0.4084730050154586,"score_spread":0.29848268158660674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605947894","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9363379,0.00011443661,0.048632823,0.0017271395,0.0113714,0.0005147856,0.0010694664,0.000027376713,0.00020466225],"genre_scores_gemma":[0.99715364,0.00003348878,0.0018892363,0.000104987026,0.00015647706,0.0000024640458,0.00022647335,0.0000063670113,0.00042684437],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99909264,0.000024200823,0.00031741444,0.000270386,0.0000943419,0.00020101698],"domain_scores_gemma":[0.9986308,0.00016726444,0.00036292884,0.0004749493,0.00033884525,0.000025178218],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0009882321,0.000074772164,0.00010105853,0.00028324092,0.0013653337,0.00046787344,0.0014387149,0.00006989108,0.000021832548],"category_scores_gemma":[0.0027391114,0.00006625587,0.000046725985,0.00007166147,0.0002263712,0.0030163808,0.00015631359,0.00013927613,0.000013694521],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014824377,0.0006383947,0.8915187,0.000009627483,0.00009090745,0.000005481061,0.00010273692,0.00022970868,0.046824086,0.04496544,0.0043227416,0.011143899],"study_design_scores_gemma":[0.0011039478,0.00006951174,0.9676663,0.00007199109,0.000016219105,0.000043315293,0.00002168715,0.0011508439,0.0005853889,0.0014540594,0.027709445,0.00010729222],"about_ca_topic_score_codex":0.0002542186,"about_ca_topic_score_gemma":0.00036884443,"teacher_disagreement_score":0.076147564,"about_ca_system_score_codex":0.00009352792,"about_ca_system_score_gemma":0.00020792807,"threshold_uncertainty_score":0.99993473},"labels":[],"label_agreement":null},{"id":"W2606005405","doi":"10.23889/ijpds.v1i1.101","title":"Privacy-Preserving Record Linkage: An international collaboration between Canada, Australia and Wales","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Record linkage; Linkage (software); Bloom filter; Computer science; Quality (philosophy); General partnership; Probabilistic logic; Data quality; Scale (ratio); Data mining; Data science; Business; Environmental health; Medicine; Geography; Marketing; Artificial intelligence","score_opus":0.4574532106082225,"score_gpt":0.5592249468859519,"score_spread":0.1017717362777294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606005405","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.947947,0.0000071965796,0.018423684,0.020073842,0.0099173905,0.0002891076,0.002872268,0.000015951546,0.000453563],"genre_scores_gemma":[0.98512787,0.000024589906,0.011446783,0.00020623204,0.0010513338,0.000004182325,0.00077336293,0.0000064333726,0.0013592303],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9950315,0.000090418005,0.000833656,0.0007099393,0.0030871779,0.00024733163],"domain_scores_gemma":[0.995011,0.00030383762,0.0011203722,0.0016617996,0.0016469425,0.00025608754],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.007205537,0.00013105755,0.00017207827,0.00037773073,0.0016032786,0.0083158575,0.012490058,0.00004428569,0.00019734514],"category_scores_gemma":[0.016199194,0.00011273362,0.00002818234,0.00018200783,0.0002251203,0.018277362,0.0027867204,0.00016005803,0.000012534822],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084813226,0.000052707488,0.72801757,0.000005408912,0.00007465884,0.000018042972,0.00022961701,0.00022609945,0.0002584015,0.020990886,0.05343196,0.19660984],"study_design_scores_gemma":[0.00037540734,0.000029112192,0.7426515,0.000027072148,0.000012172812,0.000012874874,0.00026947758,0.015035237,0.00004297481,0.016793024,0.22459845,0.00015269143],"about_ca_topic_score_codex":0.084571175,"about_ca_topic_score_gemma":0.23820555,"teacher_disagreement_score":0.19645715,"about_ca_system_score_codex":0.00024755095,"about_ca_system_score_gemma":0.000364012,"threshold_uncertainty_score":0.9996965},"labels":[],"label_agreement":null},{"id":"W2606053762","doi":"10.23889/ijpds.v1i1.211","title":"Wait times and patterns of care in the colorectal cancer diagnostic interval","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University","funders":"","keywords":"Medicine; Health care; Emergency department; Population; Confidence interval; Medical diagnosis; Colorectal cancer; Presentation (obstetrics); Cancer; Interval (graph theory); Emergency medicine; Pediatrics; Intensive care medicine; Internal medicine; Surgery; Radiology; Nursing","score_opus":0.10934818055159781,"score_gpt":0.5227615356800573,"score_spread":0.41341335512845956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606053762","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98459125,0.00019270573,0.00016327035,0.010138793,0.0032741355,0.00035584814,0.0008418304,0.0000043512186,0.00043781614],"genre_scores_gemma":[0.99782383,0.00033016503,0.0001865463,0.0011127528,0.0003643555,0.000025153397,0.00009961853,0.000004164302,0.00005339911],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99870044,0.00007128583,0.0003964638,0.00017343531,0.00046632285,0.00019207512],"domain_scores_gemma":[0.9981123,0.00066157867,0.00047434875,0.00029786333,0.00040181002,0.00005206899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013513843,0.00006132176,0.00012185952,0.00013424476,0.0010571659,0.000107368855,0.0019713386,0.000035167974,0.000082027036],"category_scores_gemma":[0.0022476385,0.000041305597,0.00002302574,0.00004055455,0.000107066415,0.0012836062,0.0005019654,0.00023339529,0.0000020288492],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054501954,0.000010096577,0.9796283,0.000035326702,0.000006048561,0.0000031105221,0.001549487,0.0000045871484,0.000025084608,0.0026675547,0.0014204088,0.014595471],"study_design_scores_gemma":[0.00047625025,0.000043396965,0.99064755,0.00017448535,0.000007896151,0.000007936152,0.0010433958,0.00054365525,0.00000957202,0.0006371386,0.0063623013,0.000046445333],"about_ca_topic_score_codex":0.0030370639,"about_ca_topic_score_gemma":0.008499446,"teacher_disagreement_score":0.014549025,"about_ca_system_score_codex":0.00023374552,"about_ca_system_score_gemma":0.00054115074,"threshold_uncertainty_score":0.81309724},"labels":[],"label_agreement":null},{"id":"W2606083779","doi":"10.23889/ijpds.v1i1.165","title":"A review of a standards-based set of information security practices applied in Data Linkage Centers","year":2017,"lang":"en","type":"review","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Linkage (software); Record linkage; Confidentiality; Business; Standardization; Population; Public relations; Knowledge management; Internet privacy; Computer security; Computer science; Political science; Medicine; Environmental health; Law","score_opus":0.657427594685601,"score_gpt":0.6472529292939032,"score_spread":0.010174665391697757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606083779","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000045139345,0.8737138,0.023270985,0.0015824116,0.003428091,0.0021124505,0.09513119,0.000011553596,0.0007450272],"genre_scores_gemma":[0.00021541986,0.9802835,0.0032787146,0.00023242722,0.00012838322,0.000013912458,0.015829334,0.000006944603,0.000011368841],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.990047,0.0002968235,0.003429453,0.00066978246,0.0053333547,0.00022362759],"domain_scores_gemma":[0.97831327,0.0011284127,0.014814632,0.0035937026,0.0020437932,0.00010616496],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.051425226,0.00021802833,0.0010841534,0.0015082839,0.0001999941,0.001081229,0.020139633,0.00008479919,0.000081151935],"category_scores_gemma":[0.061502397,0.00016231633,0.00016292812,0.00079773983,0.00028838837,0.012435411,0.003313103,0.00032204084,0.00000998492],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045580662,0.000057092053,0.00003370227,0.009835576,0.000049844504,0.0000017210378,0.000046211346,0.0000156479,1.267416e-7,0.0026058482,0.021284528,0.9660241],"study_design_scores_gemma":[0.00032429452,0.000019013318,0.000060726223,0.029577306,0.00011399667,0.000011470631,0.000056645258,0.0024213253,3.248441e-7,0.0011125669,0.96615976,0.00014258131],"about_ca_topic_score_codex":0.00023450339,"about_ca_topic_score_gemma":0.00022125315,"teacher_disagreement_score":0.9658815,"about_ca_system_score_codex":0.0002543085,"about_ca_system_score_gemma":0.0019399184,"threshold_uncertainty_score":0.9999558},"labels":[],"label_agreement":null},{"id":"W2606121086","doi":"10.23889/ijpds.v1i1.187","title":"Identifying superusers of health services with mental health and addiction problems","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Saskatchewan; University of Toronto; Centre for Addiction and Mental Health; Saskatchewan Health Authority; Saskatchewan Health Quality Council","funders":"","keywords":"Mental health; Medicine; Public health; Health care; Environmental health; Population; Family medicine; Psychiatry; Nursing","score_opus":0.1677460466381367,"score_gpt":0.5242243100452607,"score_spread":0.356478263407124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606121086","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98999846,0.00036912767,0.0025495982,0.0035828701,0.0024580713,0.00050769845,0.00044628067,0.000015612908,0.00007227471],"genre_scores_gemma":[0.99688303,0.00058078,0.0018634594,0.00012708185,0.00019229727,0.000007055333,0.00029881587,0.0000071666022,0.000040299004],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983752,0.00007272349,0.00049257977,0.00021587123,0.0006184242,0.00022523482],"domain_scores_gemma":[0.99798536,0.000034507575,0.0011817897,0.00026776828,0.00038996892,0.00014058492],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0022976345,0.000067288776,0.0001909045,0.00014609066,0.004143266,0.00021811157,0.0009775859,0.000026122189,0.000017120587],"category_scores_gemma":[0.000088711204,0.000053024414,0.000014964228,0.00006156044,0.00014614381,0.0029293713,0.00028683845,0.00013666926,0.0000012756354],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007082308,0.00003605726,0.9340833,0.00017606554,0.000035688736,3.5145666e-7,0.022986446,0.000016858072,0.00008133673,0.0037964233,0.00009700297,0.038619693],"study_design_scores_gemma":[0.0013241445,0.00016082323,0.9490366,0.0019490926,0.0000060990974,0.000004796976,0.03665611,0.004144724,0.000007385381,0.0012859551,0.0053069326,0.000117336924],"about_ca_topic_score_codex":0.0069978368,"about_ca_topic_score_gemma":0.0074940836,"teacher_disagreement_score":0.038502354,"about_ca_system_score_codex":0.00017674886,"about_ca_system_score_gemma":0.00046600073,"threshold_uncertainty_score":0.99961466},"labels":[],"label_agreement":null},{"id":"W2606164087","doi":"10.23889/ijpds.v1i1.20","title":"Teenage pregnancy: The impact of maternal adolescent childbearing and older sister’s teenage","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Adolescent Sexual and Reproductive Health","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sister; Pregnancy; Teenage pregnancy; Odds; Demography; Medicine; Logistic regression; Odds ratio; Population; Psychology; Environmental health; Sociology; Genetics","score_opus":0.24300099392000454,"score_gpt":0.5552497240977843,"score_spread":0.31224873017777977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606164087","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98909396,0.00020796205,0.0025761027,0.0028069585,0.0037196453,0.00081342366,0.00031233803,0.000015249467,0.00045435302],"genre_scores_gemma":[0.99792194,0.00018946551,0.00047836517,0.000087099754,0.00081887975,0.0000060674165,0.000033614804,0.0000103644625,0.000454182],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981159,0.000077451994,0.00051834487,0.00036167682,0.00061294145,0.0003136962],"domain_scores_gemma":[0.99750143,0.00006786434,0.001032518,0.0007752599,0.00049410184,0.0001288273],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0017674767,0.00011282979,0.0001513021,0.00013644324,0.0030716148,0.00018930672,0.0020745564,0.000044257467,0.000051716044],"category_scores_gemma":[0.0007775865,0.00006286972,0.000050835675,0.000057129226,0.00034927003,0.00168469,0.0010027466,0.00037656864,0.000005061951],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007948181,0.00007466306,0.98204696,0.000053102165,0.00003191178,0.0000022958807,0.00044325006,0.000046752506,0.00069114455,0.0015376153,0.0008012674,0.014191573],"study_design_scores_gemma":[0.00054978713,0.000036700152,0.99481463,0.00078377384,0.00000855088,0.00003359018,0.00013178166,0.002346424,0.000028640976,0.0006607775,0.00053322664,0.00007211444],"about_ca_topic_score_codex":0.000857406,"about_ca_topic_score_gemma":0.000050126546,"teacher_disagreement_score":0.014119458,"about_ca_system_score_codex":0.00016743082,"about_ca_system_score_gemma":0.0002605221,"threshold_uncertainty_score":0.9982262},"labels":[],"label_agreement":null},{"id":"W2606165586","doi":"10.23889/ijpds.v1i1.30","title":"A population-based study comparing multiple sclerosis clinic users and non-users in British Columbia, Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; University of British Columbia","funders":"","keywords":"Medicine; Specialty; Family medicine; Population; Medical prescription; Cohort; Comorbidity; Multiple sclerosis; Internal medicine; Psychiatry; Environmental health","score_opus":0.18464509580079405,"score_gpt":0.41105396570039454,"score_spread":0.2264088698996005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606165586","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971423,0.000015911932,0.00012710041,0.0007070596,0.0010189412,0.0007204322,0.00023623774,0.0000095363575,0.000022479186],"genre_scores_gemma":[0.9977238,0.000035908175,0.0016487093,0.00011923576,0.00016585579,0.000024010957,0.00019250972,0.000012789882,0.00007714369],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970931,0.000036480516,0.00058085326,0.0005080807,0.0014545833,0.0003269074],"domain_scores_gemma":[0.99793905,0.00024222296,0.00040664617,0.0005873143,0.0005889156,0.00023584209],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0017752359,0.000099399454,0.00028721264,0.0002009766,0.0013694994,0.0018404131,0.0013563854,0.000029628305,0.000031885676],"category_scores_gemma":[0.00652479,0.00013158043,0.000036223337,0.00014460276,0.00015629001,0.0015979566,0.0005348617,0.00024259268,9.39723e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006721575,0.00012501505,0.9927179,0.000009858181,0.000035737765,0.000018609016,0.000036685145,0.00019609148,0.0000994978,4.1990296e-7,0.0005916163,0.006101357],"study_design_scores_gemma":[0.0037452043,0.00006781516,0.9230538,0.00028521952,0.000015894273,0.000012294927,0.00030141062,0.07227751,0.0000034368597,0.000009866378,0.000111467765,0.00011608157],"about_ca_topic_score_codex":0.926643,"about_ca_topic_score_gemma":0.992533,"teacher_disagreement_score":0.07208142,"about_ca_system_score_codex":0.0006396486,"about_ca_system_score_gemma":0.0006481266,"threshold_uncertainty_score":0.99993056},"labels":[],"label_agreement":null},{"id":"W2606175600","doi":"10.23889/ijpds.v1i1.240","title":"Neonatal and infant readmissions for late preterm and early term babies in Ontario and England: a cohort study using linked population-level healthcare data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Infant Development and Preterm Care","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Pediatrics; New england; Population; Cohort; Gestation; Hospital discharge; Emergency medicine; Obstetrics; Pregnancy; Environmental health; Intensive care medicine","score_opus":0.15953202523804305,"score_gpt":0.41833499422771675,"score_spread":0.2588029689896737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606175600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964634,0.000058643283,0.00015979614,0.0006552057,0.0006507207,0.0010110585,0.0009841614,0.00000721908,0.000009756496],"genre_scores_gemma":[0.98742056,0.000055899938,0.0105817225,0.000056603025,0.00013922299,0.000009469051,0.0016759852,0.000009337789,0.000051217346],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99836886,0.00002018006,0.00043713028,0.0004961356,0.0004847181,0.00019296669],"domain_scores_gemma":[0.9985262,0.00007955239,0.00033635003,0.00055675907,0.0003300449,0.00017110245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014459877,0.00012785144,0.0002180955,0.0002726107,0.0007779919,0.00067592226,0.0007029665,0.00005229644,0.0000046252294],"category_scores_gemma":[0.0009969596,0.0001080311,0.000013284967,0.000043578268,0.000107193155,0.0028015247,0.0007623085,0.00019034048,4.9068923e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025228725,0.000009568616,0.9878153,0.000015102275,0.000034516837,0.000013131576,0.0017332841,0.0000017044808,0.00006775803,0.000064403546,0.000007338278,0.009985579],"study_design_scores_gemma":[0.002152362,0.00010975053,0.9839393,0.00023319868,0.000050038303,0.0002540639,0.000068660804,0.01189417,0.0000027393328,0.00038866265,0.000767403,0.00013968603],"about_ca_topic_score_codex":0.02161829,"about_ca_topic_score_gemma":0.051704466,"teacher_disagreement_score":0.030086178,"about_ca_system_score_codex":0.0001362799,"about_ca_system_score_gemma":0.00030719917,"threshold_uncertainty_score":0.98489684},"labels":[],"label_agreement":null},{"id":"W2606176380","doi":"10.23889/ijpds.v1i1.199","title":"Are There Long-term Academic Benefits of Full-Day Kindergarten? A Population-Based Analysis","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Children's Hospital Research Institute of Manitoba; University of Manitoba; Manitoba Health","funders":"","keywords":"Propensity score matching; Confounding; Numeracy; Population; Equity (law); Demography; Socioeconomic status; Logistic regression; Medicine; Psychology; Environmental health; Political science","score_opus":0.10357620480811473,"score_gpt":0.4361632002887608,"score_spread":0.3325869954806461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606176380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9836274,0.000086564905,0.006755765,0.0058801286,0.002895964,0.0002384829,0.000248952,0.000022851718,0.0002439003],"genre_scores_gemma":[0.9963541,0.00006372211,0.0021906365,0.00020734938,0.00059367047,0.000005075956,0.00032856225,0.0000074423056,0.00024941645],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99707687,0.00007040073,0.0005554094,0.00038062007,0.0016463448,0.00027033818],"domain_scores_gemma":[0.9961179,0.00015088993,0.0017746959,0.00061413075,0.0011340427,0.00020836579],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002860024,0.00011334273,0.00018811895,0.0006200347,0.0021436235,0.0008235595,0.0036522083,0.00008340981,0.00020312646],"category_scores_gemma":[0.0035564895,0.00010579324,0.00011241869,0.00042692,0.00024913103,0.002760811,0.00019853353,0.00017879864,0.0000074572613],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015344422,0.00003642454,0.98459095,0.000002155141,0.00007870054,9.1124843e-7,0.00041866352,0.0015128568,0.000017192766,0.0033625795,0.00018877054,0.009775453],"study_design_scores_gemma":[0.00027676104,0.000008899625,0.9963364,0.0000717009,0.000064787506,0.000002389174,0.00019771572,0.0016605491,0.000015957236,0.0008255585,0.00041058107,0.0001287228],"about_ca_topic_score_codex":0.0014714631,"about_ca_topic_score_gemma":0.006407382,"teacher_disagreement_score":0.012726733,"about_ca_system_score_codex":0.0002466029,"about_ca_system_score_gemma":0.0006781126,"threshold_uncertainty_score":0.99915546},"labels":[],"label_agreement":null},{"id":"W2606182731","doi":"10.23889/ijpds.v1i1.404","title":"Political and Policy Arguments for Integrated Data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Institute for Clinical Evaluative Sciences; Public Health Ontario; University of Toronto; St. Michael's Hospital","funders":"","keywords":"Integrated care; Politics; Accountability; Opposition (politics); Survey data collection; Public administration; Public relations; Argument (complex analysis); Health care; Data collection; Political science; Data science; Sociology; Law; Computer science; Medicine; Social science","score_opus":0.31081874857909986,"score_gpt":0.47203018240455735,"score_spread":0.1612114338254575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606182731","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08154266,0.00034325998,0.46853253,0.36497983,0.016536606,0.00198501,0.054651085,0.00007203533,0.011356972],"genre_scores_gemma":[0.9870713,0.00005298241,0.009891707,0.0009919624,0.000797513,0.0000074021896,0.00080412487,0.0000075621206,0.00037544474],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987616,0.0000049186074,0.00042196456,0.00041181152,0.00011173426,0.00028799695],"domain_scores_gemma":[0.99833,0.00004504685,0.0004110892,0.0008888539,0.00015607478,0.00016896105],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0019519625,0.00007139007,0.000120018274,0.00033050476,0.00077428744,0.0010782129,0.0032750252,0.000028872799,0.000012733456],"category_scores_gemma":[0.004589033,0.00007227159,0.000020114192,0.00005454152,0.00013948233,0.0032390342,0.0010089866,0.000073235926,0.000009430557],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015184919,0.000018373627,0.0125033455,0.0000056523495,0.00001815751,5.2486786e-7,0.000011838824,0.000002240531,0.0000035214882,0.97319955,0.0015647255,0.012656872],"study_design_scores_gemma":[0.00082812324,0.000043913395,0.11059718,0.000030097472,0.0000054286797,0.000024171557,0.0000347463,0.08693656,0.00000786692,0.28432617,0.5170153,0.00015044493],"about_ca_topic_score_codex":0.0040959097,"about_ca_topic_score_gemma":0.00019254962,"teacher_disagreement_score":0.90552866,"about_ca_system_score_codex":0.00017018206,"about_ca_system_score_gemma":0.00011417004,"threshold_uncertainty_score":0.99995875},"labels":[],"label_agreement":null},{"id":"W2606219717","doi":"10.23889/ijpds.v1i1.62","title":"Exploring the Impact of Health Insurance on Health Care Utilization and Outcome Using Electronic Medical Record Data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Reimbursement; Odds ratio; Comorbidity; Cirrhosis; Logistic regression; Health care; Medical record; Emergency medicine; Population; Confounding; Internal medicine; Intensive care medicine; Environmental health","score_opus":0.6137570515710665,"score_gpt":0.5800979805447342,"score_spread":0.033659071026332366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606219717","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9835175,0.00038421154,0.005466695,0.0085074315,0.0011948626,0.00040426725,0.000455652,0.00001187349,0.00005748474],"genre_scores_gemma":[0.9975409,0.00097204203,0.000527281,0.00018666332,0.00022407208,0.0000019790145,0.0005341107,0.000007222293,0.000005758136],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979457,0.000037905604,0.0004720451,0.00030204037,0.0010150375,0.00022726423],"domain_scores_gemma":[0.9979104,0.000050625353,0.00071383273,0.00097641785,0.00021939789,0.00012932104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022552004,0.00008446208,0.0001670211,0.00016697605,0.0007823341,0.00027945262,0.0018687911,0.00001198384,0.000014943057],"category_scores_gemma":[0.0016764955,0.00005712229,0.00003189629,0.00009103371,0.00018096797,0.0025436094,0.0005810251,0.00015165981,4.216164e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021306645,0.000082947445,0.45726717,0.00008690883,0.000091350325,0.0000036244248,0.00022351272,0.00045065233,0.000013044681,0.0040154336,0.0006394583,0.5369128],"study_design_scores_gemma":[0.00075930334,0.00018307685,0.9300688,0.00031380603,0.00000888863,0.000045774836,0.00021026484,0.06724065,0.0000016445265,0.00028143844,0.00083236495,0.000054003496],"about_ca_topic_score_codex":0.002256469,"about_ca_topic_score_gemma":0.00031889224,"teacher_disagreement_score":0.5368588,"about_ca_system_score_codex":0.0005857211,"about_ca_system_score_gemma":0.0015118977,"threshold_uncertainty_score":0.601716},"labels":[],"label_agreement":null},{"id":"W2606282829","doi":"10.23889/ijpds.v1i1.209","title":"Colonoscopy resource availability and colonoscopy utilization in Ontario, Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University","funders":"","keywords":"Colonoscopy; Medicine; Specialty; Referral; Colorectal cancer; Population; Internal medicine; Family medicine; Environmental health; Cancer","score_opus":0.10428512348528718,"score_gpt":0.3938136068972294,"score_spread":0.2895284834119422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606282829","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954192,0.000024764942,0.0007967162,0.0016178429,0.0013939576,0.00021442772,0.000050571856,0.000007965579,0.00047453935],"genre_scores_gemma":[0.9975701,0.000009638786,0.0017193586,0.00016487198,0.00012420253,0.0000053645613,0.00011944701,0.0000044004128,0.00028261356],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987234,0.000014151834,0.00026620438,0.00030396998,0.0005476893,0.00014459841],"domain_scores_gemma":[0.9988975,0.000048930364,0.00025218312,0.00037928304,0.00030632934,0.000115780735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092058745,0.000069607115,0.0001116689,0.00013934367,0.0005623424,0.00032250097,0.0005860658,0.000031967083,0.000043774795],"category_scores_gemma":[0.0014638454,0.00006651851,0.0000144255,0.00007072744,0.00013291664,0.0010876381,0.00020275288,0.0001737391,4.4677918e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034372297,0.00003266692,0.9838054,0.0000061578858,0.000011461524,0.000011543393,0.000081727965,0.00008126326,0.00027466923,0.00016244872,0.0015122858,0.0105831195],"study_design_scores_gemma":[0.000798063,0.00031410958,0.96063185,0.00006280918,0.000009583977,0.00010258287,0.00003364016,0.014171605,0.0002888484,0.00020197676,0.023318825,0.0000661219],"about_ca_topic_score_codex":0.83718914,"about_ca_topic_score_gemma":0.9828334,"teacher_disagreement_score":0.14564426,"about_ca_system_score_codex":0.0011127256,"about_ca_system_score_gemma":0.0013431151,"threshold_uncertainty_score":0.43251398},"labels":[],"label_agreement":null},{"id":"W2606329276","doi":"10.23889/ijpds.v1i1.109","title":"Maternal age and child development outcomes at age five in Australian Aboriginal and non-Aboriginal children: a population data linkage study","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Birth, Development, and Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Manitoba Health","funders":"","keywords":"Medicine; Demography; Population; Cohort; Vulnerability (computing); Poisson regression; Pediatrics; Environmental health","score_opus":0.06747148968451555,"score_gpt":0.4428207737012195,"score_spread":0.375349284016704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606329276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960273,0.000019611094,0.0001626007,0.0017152609,0.0010186913,0.0006597246,0.000297834,0.000013874156,0.0000851016],"genre_scores_gemma":[0.9868287,0.0006499822,0.010380038,0.0001942865,0.00033067187,0.0000082043525,0.0014204194,0.000014373323,0.00017333873],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971473,0.000026565202,0.0006895272,0.00072326313,0.0010577529,0.0003555806],"domain_scores_gemma":[0.9981916,0.000025982712,0.00054202863,0.0007785803,0.00017100977,0.0002908068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017646475,0.0002115438,0.00031071392,0.00045225135,0.0012580213,0.00081049744,0.0015947076,0.000062894076,0.00002072079],"category_scores_gemma":[0.0002068327,0.00017822601,0.000019852188,0.000099680605,0.00017066624,0.002593275,0.0006505037,0.0003127399,0.000004399306],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014017368,0.0001227769,0.994973,0.000021712567,0.000050911975,0.0001490115,0.00049219455,0.0000042331244,0.000031359752,0.0006997336,0.000104483435,0.0032103942],"study_design_scores_gemma":[0.0027561777,0.000086132175,0.993872,0.00026564373,0.00003084823,0.00040219803,0.00007222553,0.000989598,0.000013418907,0.0003648841,0.00096009986,0.00018680548],"about_ca_topic_score_codex":0.0036023364,"about_ca_topic_score_gemma":0.0064268173,"teacher_disagreement_score":0.010217437,"about_ca_system_score_codex":0.0003474576,"about_ca_system_score_gemma":0.00030181115,"threshold_uncertainty_score":0.96758103},"labels":[],"label_agreement":null},{"id":"W2606338355","doi":"10.23889/ijpds.v1i1.166","title":"A six-year trend of the healthcare cost of arthritis in a population-based cohort of older women","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Pharmaceutical Benefits Scheme; Medicine; Health care; Percentile; Cohort; Population; Medical prescription; Statistics; Environmental health; Nursing; Economics","score_opus":0.31354456300975686,"score_gpt":0.4864211403152134,"score_spread":0.17287657730545652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606338355","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9853314,0.00009631704,0.0012219558,0.008273584,0.0014698467,0.000537379,0.002974426,0.0000027926394,0.00009228261],"genre_scores_gemma":[0.9978467,0.000033741417,0.0015384867,0.00029559966,0.00010483719,0.000020604939,0.00012726583,0.00000746732,0.000025291503],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99633205,0.00007791317,0.002751555,0.00029062107,0.00035619043,0.00019165647],"domain_scores_gemma":[0.9934965,0.00027012793,0.0050806645,0.0007778537,0.00029508557,0.00007980136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012140611,0.00007880569,0.0004324093,0.0004483783,0.0002565285,0.0000940972,0.0018668702,0.00004834493,0.00007706131],"category_scores_gemma":[0.0067769233,0.00008022481,0.0000690215,0.00015786343,0.00017700622,0.0013842876,0.00015751578,0.00010022245,0.0000027782653],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000197984,0.000047902307,0.9750877,0.000040119718,0.00001359641,1.09051726e-7,0.00025610067,0.00083754765,0.0000076186307,0.022794254,0.00017338485,0.0007218555],"study_design_scores_gemma":[0.00085935823,0.000025598127,0.977647,0.00024881624,0.0000015740085,0.0000028457093,0.00014408951,0.01494214,0.000016324864,0.005583828,0.00045876595,0.00006962631],"about_ca_topic_score_codex":0.0054398547,"about_ca_topic_score_gemma":0.0024145448,"teacher_disagreement_score":0.017210426,"about_ca_system_score_codex":0.00046510703,"about_ca_system_score_gemma":0.00030732554,"threshold_uncertainty_score":0.8223469},"labels":[],"label_agreement":null},{"id":"W2606345598","doi":"10.23889/ijpds.v1i1.207","title":"Integrated KT 2.0: The next generation of teamwork","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Sciences Research and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"George & Fay Yee Centre for Healthcare Innovation; Manitoba Health","funders":"","keywords":"Teamwork; Government (linguistics); Team effectiveness; Work (physics); Population; Scope (computer science); Scale (ratio); Conceptualization; Health care; Psychology; Project team; Psychological safety; Public relations; Medical education; Knowledge management; Political science; Medicine; Engineering; Applied psychology; Computer science; Environmental health","score_opus":0.6950282599346479,"score_gpt":0.6308163669983619,"score_spread":0.06421189293628604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606345598","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9365818,0.000058280046,0.014433754,0.024450466,0.022030998,0.00082393317,0.0002636384,0.00001680179,0.0013403266],"genre_scores_gemma":[0.9925359,0.000098858734,0.0040594507,0.00038838343,0.0020930807,0.000021389116,0.00020832192,0.000005083197,0.0005895153],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975974,0.0001274166,0.0005832556,0.00024902925,0.0011027441,0.0003401479],"domain_scores_gemma":[0.9960759,0.00030059402,0.000862453,0.0008125987,0.0017840827,0.00016433896],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.0068073734,0.00006661415,0.00009442058,0.00020386123,0.005391281,0.00045376542,0.0043470473,0.00004507674,0.0001802739],"category_scores_gemma":[0.010234241,0.000041448257,0.000029465147,0.00019510405,0.00038751392,0.0039394884,0.00044204836,0.00033950154,0.000029260422],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022058733,0.00015633427,0.5129718,0.000050259765,0.000049354243,0.000002131904,0.003406758,0.00037366216,0.01898524,0.03434817,0.22943647,0.19999921],"study_design_scores_gemma":[0.0006781208,0.000084018124,0.6479877,0.00021434191,0.000010134023,0.000014995547,0.002137756,0.19448669,0.00020327036,0.004325056,0.14971653,0.00014139555],"about_ca_topic_score_codex":0.0018809331,"about_ca_topic_score_gemma":0.000699021,"teacher_disagreement_score":0.19985782,"about_ca_system_score_codex":0.00022972097,"about_ca_system_score_gemma":0.001661523,"threshold_uncertainty_score":0.99810296},"labels":[],"label_agreement":null},{"id":"W2606372922","doi":"10.23889/ijpds.v1i1.388","title":"A Federated Data Linkage Strategy to Support Population Health Research in Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Partnership Against Cancer","funders":"","keywords":"Cohort; Custodians; Biobank; Medicine; Data quality; Cohort study; Government (linguistics); Family medicine; Health care; Gerontology; Business; Geography; Political science; Marketing","score_opus":0.7997039661952389,"score_gpt":0.6484931996867838,"score_spread":0.1512107665084551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606372922","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74512565,0.00006436416,0.070085704,0.14353618,0.019024866,0.0028652481,0.01691315,0.000046213532,0.0023386355],"genre_scores_gemma":[0.9928065,0.00002124555,0.0025343723,0.0010507766,0.0003109405,0.0000058511737,0.0028793064,0.0000074169893,0.0003835773],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9908847,0.00028588984,0.0012755326,0.0010652874,0.005934508,0.0005540469],"domain_scores_gemma":[0.9942905,0.0004715559,0.000827544,0.002696949,0.001325409,0.00038808657],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.040605534,0.00011747554,0.00022330903,0.0009623219,0.0021715995,0.006612808,0.016638158,0.000029035744,0.00012651585],"category_scores_gemma":[0.014900006,0.000100647834,0.00002020223,0.0006891058,0.000114736846,0.010000882,0.0045144167,0.0003049215,0.000044926328],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012008201,0.00008624342,0.13090374,0.0000071249033,0.000016823911,0.00004759506,0.000092572576,0.0021790105,0.00003099335,0.0089425715,0.17148416,0.6860891],"study_design_scores_gemma":[0.0005193102,0.00010414002,0.81363565,0.00007040915,0.0000020482485,0.000026102,0.000695856,0.08832281,0.0000053438926,0.011961986,0.08448881,0.00016751373],"about_ca_topic_score_codex":0.82347137,"about_ca_topic_score_gemma":0.95942444,"teacher_disagreement_score":0.68592155,"about_ca_system_score_codex":0.0012350902,"about_ca_system_score_gemma":0.0036415989,"threshold_uncertainty_score":0.99912745},"labels":[],"label_agreement":null},{"id":"W2606377163","doi":"10.23889/ijpds.v1i1.377","title":"High school graduation – the impact of older siblings’ educational achievement","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cognitive Abilities and Testing","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Graduation (instrument); Sibling; Demography; Odds; Logistic regression; Gerontology; Confounding; Academic achievement; Odds ratio; Birth order; Medicine; Psychology; Developmental psychology; Population; Sociology","score_opus":0.1427579719821722,"score_gpt":0.49175385595860843,"score_spread":0.3489958839764362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606377163","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9843859,0.00002448349,0.004259976,0.0061459043,0.003919004,0.00024850763,0.00037618377,0.0000062812383,0.0006337486],"genre_scores_gemma":[0.9970297,0.000005241916,0.0014009112,0.00007031028,0.0008877499,0.000012525237,0.00023566106,0.00000638255,0.00035151598],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99854434,0.000031903244,0.00037653142,0.0002567328,0.0006173216,0.00017317022],"domain_scores_gemma":[0.9971528,0.0002793629,0.00075704284,0.0006247403,0.0011078304,0.00007822373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017075926,0.00008271179,0.00008352625,0.00018829758,0.0010041733,0.0005584503,0.0023128346,0.000021679663,0.0007146306],"category_scores_gemma":[0.003823906,0.000056273533,0.0000757356,0.000096326075,0.00025142723,0.0017440604,0.00031235523,0.00012753607,0.000015107765],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011997828,0.00028042652,0.86382174,0.0000034403752,0.00015976884,0.000001190424,0.0004419224,0.0005155795,0.0008291928,0.07418127,0.0059760176,0.053669453],"study_design_scores_gemma":[0.0004624549,0.00005266366,0.9781334,0.00003425637,0.000011852779,0.00003315175,0.00012394313,0.0024028902,0.000021337772,0.01846933,0.0001900788,0.00006466646],"about_ca_topic_score_codex":0.0028696666,"about_ca_topic_score_gemma":0.000054764867,"teacher_disagreement_score":0.11431162,"about_ca_system_score_codex":0.00015299725,"about_ca_system_score_gemma":0.0002563399,"threshold_uncertainty_score":0.7824704},"labels":[],"label_agreement":null},{"id":"W2606391515","doi":"10.23889/ijpds.v1i1.102","title":"How access, appropriateness, and quality of care affect patient outcomes for time-sensitive medical emergencies in British Columbia, Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Emergency medicine; Medical emergency; Stroke (engine); Proportional hazards model; Population; Hazard ratio; Rurality; Emergency medical services; Medical record; Environmental health; Confidence interval; Rural area; Internal medicine","score_opus":0.12601700127895868,"score_gpt":0.3859531223420566,"score_spread":0.25993612106309794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606391515","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9838186,0.00010353491,0.0020331382,0.008325089,0.0016931343,0.00036121052,0.0035759592,0.000002837603,0.00008653186],"genre_scores_gemma":[0.9987951,0.00008371943,0.0005815329,0.0002167952,0.00006516464,0.000011260271,0.00014447478,0.0000041317357,0.00009782949],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988648,0.000012967131,0.00046615684,0.00026096616,0.00024004755,0.00015505144],"domain_scores_gemma":[0.99867123,0.00007532347,0.0006654207,0.00023954362,0.00026359467,0.000084898995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013611829,0.000047619644,0.00020268421,0.000084272215,0.0003583976,0.0008649796,0.0010423583,0.000029714975,0.000013329905],"category_scores_gemma":[0.0043730973,0.00006536493,0.000029777131,0.000046106674,0.00009909161,0.0014160167,0.00038640868,0.000057733225,2.0039478e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012658055,0.000021937798,0.9665239,0.000049351856,0.000023594745,0.0000027664594,0.000089547044,0.000017707835,0.0000027306778,0.007978319,0.00081579166,0.024461694],"study_design_scores_gemma":[0.00039353242,0.000022997336,0.98611236,0.000042634794,0.0000016202835,0.0000032581027,0.00014001149,0.0032540164,0.000005891271,0.0025161353,0.0074233096,0.00008423573],"about_ca_topic_score_codex":0.8971412,"about_ca_topic_score_gemma":0.96977884,"teacher_disagreement_score":0.0726376,"about_ca_system_score_codex":0.00018932836,"about_ca_system_score_gemma":0.00025340638,"threshold_uncertainty_score":0.8341018},"labels":[],"label_agreement":null},{"id":"W2606403132","doi":"10.23889/ijpds.v1i1.177","title":"Identifying superusers of health services with mental health and addiction problems: Putting the Canadian Institutes of Health Research Strategy for Patient Oriented Research into action","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Mental Health and Patient Involvement","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Saskatchewan; Saskatchewan Health Authority; Saskatchewan Health Quality Council","funders":"","keywords":"Ivory tower; Population; Mental health; Public relations; Health care; Addiction; Psychology; Medicine; Nursing; Medical education; Political science; Psychiatry; Environmental health","score_opus":0.7432422408962178,"score_gpt":0.6309240195916693,"score_spread":0.1123182213045485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606403132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96931314,0.00083879405,0.0014276621,0.018158246,0.0036889603,0.005301151,0.0012003888,0.000011065046,0.000060571572],"genre_scores_gemma":[0.9939193,0.0004560981,0.0034237169,0.00038154377,0.00015313331,0.00009284043,0.001539832,0.000011036448,0.000022482694],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99502325,0.00073296577,0.001238938,0.0003858193,0.0018860851,0.0007329383],"domain_scores_gemma":[0.99492055,0.00028741983,0.0017626861,0.00046800633,0.0021328628,0.00042847137],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.02344714,0.00010053353,0.00021689643,0.0007054361,0.016527286,0.00020376247,0.0011400586,0.00004552404,0.000006947777],"category_scores_gemma":[0.00037153167,0.00007298502,0.000021914053,0.00030378855,0.0004373968,0.001978267,0.00035908105,0.0004816909,8.270741e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007207359,0.0002776288,0.5349014,0.004773901,0.00010132948,5.0088005e-7,0.058979988,0.00032151985,0.0001976498,0.014061167,0.0035426759,0.38212156],"study_design_scores_gemma":[0.007126814,0.00932455,0.61413974,0.028986199,0.00001572917,0.000035326422,0.19241433,0.03769604,0.00016823999,0.011151167,0.09851352,0.000428327],"about_ca_topic_score_codex":0.4525095,"about_ca_topic_score_gemma":0.53259504,"teacher_disagreement_score":0.3816932,"about_ca_system_score_codex":0.0019820384,"about_ca_system_score_gemma":0.0065523037,"threshold_uncertainty_score":0.99907964},"labels":[],"label_agreement":null},{"id":"W2606419356","doi":"10.23889/ijpds.v1i1.134","title":"Differences in the breast cancer diagnostic process across stage groups in Ontario, Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Dalhousie University; Cancer Care Ontario; University Health Network; Queen's University","funders":"","keywords":"Medicine; Stage (stratigraphy); Breast cancer; Ambulatory; Cancer; Biopsy; Confidence interval; Retrospective cohort study; Internal medicine; Pediatrics","score_opus":0.1609249610777704,"score_gpt":0.45024703725357834,"score_spread":0.28932207617580796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606419356","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9929601,0.00003246658,0.00008938656,0.0051072836,0.0011544011,0.0001847447,0.00038714777,0.0000021718342,0.00008232334],"genre_scores_gemma":[0.99899334,0.000025196057,0.00007780888,0.00053880434,0.0002023255,0.000017029033,0.000062270854,0.000003027398,0.00008017578],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99805546,0.000013176624,0.0002894813,0.00024645432,0.0011449005,0.00025051975],"domain_scores_gemma":[0.99891156,0.000104527375,0.0002593186,0.00034778283,0.00030201575,0.000074789525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010889496,0.00007897495,0.000118100485,0.00007382471,0.0004816521,0.00052937353,0.002233481,0.000020725198,0.00006550856],"category_scores_gemma":[0.001217538,0.000053327753,0.000017760927,0.00010451293,0.000121826946,0.0019412016,0.0001652415,0.0002514274,4.1201596e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007537393,0.000019969593,0.9961219,0.0000037764403,0.0000050607005,0.00006602576,0.00036750492,0.00015086457,0.000009831452,0.00017120046,0.0002108166,0.0027977154],"study_design_scores_gemma":[0.0005399179,0.000016846985,0.99489075,0.0002419109,0.000005032339,0.00020020362,0.00065620756,0.0026663824,0.000005322082,0.00024404077,0.00046830572,0.00006509665],"about_ca_topic_score_codex":0.9645586,"about_ca_topic_score_gemma":0.99732965,"teacher_disagreement_score":0.032771062,"about_ca_system_score_codex":0.0008059659,"about_ca_system_score_gemma":0.0016013592,"threshold_uncertainty_score":0.5104761},"labels":[],"label_agreement":null},{"id":"W2606421450","doi":"10.23889/ijpds.v1i1.48","title":"Adolescent pregnancy termination and childbearing – the impact of an older sister’s pregnancy outcome","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Adolescent Sexual and Reproductive Health","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Sister; Pregnancy; Teenage pregnancy; Medicine; Odds; Odds ratio; Cohort; Demography; Logistic regression; Obstetrics; Fertility; Psychology; Population; Environmental health; Internal medicine; Sociology; Genetics","score_opus":0.3255927237238956,"score_gpt":0.5921646120899267,"score_spread":0.2665718883660311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606421450","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.990749,0.00013754441,0.0025309033,0.0019149571,0.0032028495,0.0009851378,0.00022438186,0.00001558111,0.00023965862],"genre_scores_gemma":[0.99828017,0.0000570169,0.0006515264,0.000056099954,0.00052712124,0.000009927103,0.00007536453,0.000009577333,0.00033317975],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99809664,0.00009754052,0.0005903771,0.00037421743,0.000576343,0.00026485286],"domain_scores_gemma":[0.99714506,0.000062122985,0.0011647634,0.0008388267,0.00066078,0.00012843449],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0015291038,0.00010762833,0.00014542913,0.00014423768,0.0028909207,0.00016614041,0.0018104423,0.000047478203,0.000024281964],"category_scores_gemma":[0.0012630122,0.00006385363,0.00004293769,0.00005907885,0.00025772117,0.003026518,0.00061603007,0.0003181691,0.0000023331152],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041489922,0.00012702734,0.9507183,0.000052364052,0.000014788154,0.0000013312098,0.00061055186,0.000038516726,0.00033216013,0.0008818201,0.0000771769,0.047104508],"study_design_scores_gemma":[0.00056645885,0.00006251769,0.99183875,0.0010089618,0.000008667578,0.000024341532,0.00019683965,0.0054223984,0.000017187347,0.00068199623,0.00009648204,0.00007541491],"about_ca_topic_score_codex":0.0003445672,"about_ca_topic_score_gemma":0.00006433403,"teacher_disagreement_score":0.047029093,"about_ca_system_score_codex":0.00015110553,"about_ca_system_score_gemma":0.00023349679,"threshold_uncertainty_score":0.9984072},"labels":[],"label_agreement":null},{"id":"W2606433617","doi":"10.23889/ijpds.v1i1.208","title":"Developing population segments with different levels of complexity and primary health care needs: An analysis using health administrative data in British Columbia, Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Population; Health care; Medicine; Vulnerability (computing); Family medicine; Gerontology; Nursing; Environmental health; Computer science","score_opus":0.2786388582475221,"score_gpt":0.4718001715515206,"score_spread":0.1931613133039985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606433617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9888664,0.000072768315,0.006049828,0.0010617293,0.00022573558,0.00038547826,0.0033222171,0.00000481173,0.0000110417495],"genre_scores_gemma":[0.98157895,0.000026056969,0.011771431,0.00024384931,0.00005892377,0.0000015627378,0.0063046794,0.000006099672,0.000008435965],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978905,0.000041133386,0.0005144239,0.0003841612,0.000967572,0.00020223623],"domain_scores_gemma":[0.9979787,0.00002085109,0.0008645525,0.00066398026,0.00030065663,0.0001712945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069245504,0.00008290004,0.00030015755,0.00022860675,0.0006574905,0.0007970945,0.001052921,0.000013870439,0.000011900737],"category_scores_gemma":[0.00015990325,0.000099607794,0.000015219856,0.00020646873,0.00015883415,0.0023139385,0.00047092978,0.000085728214,1.1439162e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037733847,0.000047935104,0.98826796,0.000096646654,0.00012115629,0.000009213907,0.0001294889,0.00014939082,0.0000032853075,0.00020739206,0.000039414153,0.010890372],"study_design_scores_gemma":[0.00088431465,0.00007852333,0.97775084,0.00032815486,0.000060881484,0.000037293103,0.0013065535,0.019308832,6.7967187e-7,0.00012428133,0.000031370746,0.00008825806],"about_ca_topic_score_codex":0.83488804,"about_ca_topic_score_gemma":0.9836304,"teacher_disagreement_score":0.14874236,"about_ca_system_score_codex":0.0018607258,"about_ca_system_score_gemma":0.0032254404,"threshold_uncertainty_score":0.76864004},"labels":[],"label_agreement":null},{"id":"W2606482640","doi":"10.23889/ijpds.v1i1.205","title":"Evaluating the Completness of Physician Billing Claims: A Proof-of-Concept Study","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Calgary; Dalhousie University; University of Manitoba","funders":"","keywords":"Medical prescription; Medicine; Remuneration; Payment; Logistic regression; Cohort; Family medicine; Completeness (order theory); Actuarial science; Business; Finance; Internal medicine; Nursing; Mathematics","score_opus":0.4954518403589558,"score_gpt":0.510611235372279,"score_spread":0.015159395013323251,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606482640","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9471821,0.000082271115,0.041410334,0.0062339194,0.003080601,0.00074132776,0.00064284285,0.000005262354,0.00062133296],"genre_scores_gemma":[0.997869,0.000003915729,0.0017061896,0.000105976345,0.00025083916,0.000007299196,0.000021902357,0.0000043453992,0.000030509556],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877334,0.000017321048,0.00063341367,0.00022019417,0.0002257739,0.00012996823],"domain_scores_gemma":[0.9975764,0.000064610416,0.0014283645,0.0006066739,0.00029108956,0.000032864136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036570644,0.000055148525,0.00014737686,0.00016934761,0.0007052571,0.00023880771,0.0025780532,0.000012094209,0.0000106779335],"category_scores_gemma":[0.0010698917,0.000044900655,0.00003940124,0.000091086324,0.00017301229,0.0012645401,0.00039759514,0.0000763897,0.0000014438481],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007916333,0.0004437858,0.1126185,0.000035957928,0.00015285063,0.0000013294685,0.003026514,0.010748355,0.000104249535,0.6535674,0.0002037041,0.2190182],"study_design_scores_gemma":[0.0014906311,0.00049589993,0.40119174,0.00013796474,0.00002113271,0.0000065464324,0.0010645594,0.46100706,0.00034578508,0.12767705,0.0063299565,0.00023167109],"about_ca_topic_score_codex":0.0020633305,"about_ca_topic_score_gemma":0.00013562989,"teacher_disagreement_score":0.52589035,"about_ca_system_score_codex":0.00006085843,"about_ca_system_score_gemma":0.00006006444,"threshold_uncertainty_score":0.54243386},"labels":[],"label_agreement":null},{"id":"W2606492162","doi":"10.23889/ijpds.v1i1.70","title":"Multinational Population-Based Health Surveys Linked to Outcome Data: An Untapped Resource","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Promotion and Cardiovascular Prevention","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada; Ottawa Hospital","funders":"","keywords":"National Health Interview Survey; Comparability; Environmental health; Medicine; Population health; Cohort; Population; Community health; Demography; Residence; Gerontology; Public health","score_opus":0.25535939234222366,"score_gpt":0.5237605528973124,"score_spread":0.2684011605550887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606492162","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30019134,0.00003909093,0.6545005,0.03552914,0.0052999975,0.0018042241,0.0023650266,0.000116862284,0.00015381066],"genre_scores_gemma":[0.951183,0.0000069340617,0.028735535,0.0019439007,0.0010835967,0.000008582058,0.0167394,0.000022092529,0.000276922],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99543387,0.00048626517,0.0009274965,0.0007859893,0.002000407,0.000366],"domain_scores_gemma":[0.99511886,0.000085592736,0.0007784294,0.0023578715,0.0010337381,0.0006255065],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.02187464,0.00015775427,0.00029771752,0.0005153829,0.0018520933,0.00078442646,0.0032460475,0.00006970668,0.0000665206],"category_scores_gemma":[0.0049891374,0.00014858202,0.00010192855,0.00018928976,0.00008426229,0.003569806,0.00061068573,0.00026531567,0.00002353833],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011304921,0.00037354897,0.621043,0.00006687965,0.00008602238,0.000012596601,0.00008525311,0.0017685484,0.00018332042,0.0010543911,0.001525504,0.37368783],"study_design_scores_gemma":[0.0016263472,0.00011623475,0.90500385,0.0001309875,0.000021037407,0.0000779079,0.00002686141,0.07756182,0.000004120417,0.00015395744,0.015141925,0.00013496635],"about_ca_topic_score_codex":0.0014384113,"about_ca_topic_score_gemma":0.00063215353,"teacher_disagreement_score":0.6509917,"about_ca_system_score_codex":0.00051617884,"about_ca_system_score_gemma":0.0007786772,"threshold_uncertainty_score":0.99944735},"labels":[],"label_agreement":null},{"id":"W2606501131","doi":"10.23889/ijpds.v1i1.76","title":"Social Data Linkage Environment","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Identifier; Record linkage; Computer science; Index (typography); Personally identifiable information; Internet privacy; Unique identifier; Database; World Wide Web; Computer security; Sociology; Demography","score_opus":0.6447609076066653,"score_gpt":0.5948565105111473,"score_spread":0.04990439709551797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606501131","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0686361,0.00008947932,0.75465643,0.12021157,0.02845367,0.0010815688,0.017803043,0.0000806437,0.0089874705],"genre_scores_gemma":[0.98170173,0.000050927243,0.01261764,0.00055342447,0.0015636353,0.0000031787486,0.0016762404,0.000007821719,0.0018254175],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99439365,0.000061738654,0.00070402917,0.0008211129,0.0037719067,0.00024759164],"domain_scores_gemma":[0.9946865,0.00021020012,0.0010406863,0.0035748777,0.00035827735,0.00012948828],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.015294448,0.0001006736,0.00014019987,0.00029013483,0.0027492808,0.0064321063,0.030217176,0.000033285272,0.00027872773],"category_scores_gemma":[0.010137336,0.00008004458,0.00004608919,0.0000947729,0.0004193577,0.013843622,0.009070815,0.0001391163,0.00019996049],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008495343,0.00016854006,0.017014695,0.0000029901912,0.00006492607,0.000021924205,0.00020701939,0.00020713276,0.00024557766,0.09025483,0.23300697,0.65872043],"study_design_scores_gemma":[0.00043465526,0.000016160377,0.1680013,0.00000936597,0.000012986348,0.000018951234,0.00012934791,0.036161862,0.000015023571,0.045548853,0.74951345,0.0001380514],"about_ca_topic_score_codex":0.00013396963,"about_ca_topic_score_gemma":0.000083854946,"teacher_disagreement_score":0.9130656,"about_ca_system_score_codex":0.00010213881,"about_ca_system_score_gemma":0.00010720678,"threshold_uncertainty_score":0.9999492},"labels":[],"label_agreement":null},{"id":"W2606528786","doi":"10.23889/ijpds.v1i1.356","title":"The Canadian Chronic Disease Surveillance System: The Benefits and Challenges of a Distributed Model for National Disease Surveillance","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Promotion and Cardiovascular Prevention","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ministry of Health; University of Manitoba","funders":"","keywords":"Disease; Population; Disease surveillance; Medicine; Disease registry; Record linkage; Public health; Health care; Protocol (science); Public health surveillance; Family medicine; Environmental health; Medical emergency; Alternative medicine; Pathology; Political science","score_opus":0.13289524754757503,"score_gpt":0.3986012104681609,"score_spread":0.26570596292058585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606528786","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2996008,0.03823996,0.23519936,0.35731724,0.012154399,0.008832606,0.048117734,0.00011151238,0.00042636527],"genre_scores_gemma":[0.99772215,0.0011037951,0.0001708792,0.000052016552,0.0003705376,0.000029046121,0.0004979994,0.000006916732,0.0000466332],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9982163,0.00007892103,0.00032271867,0.00025274776,0.00092230586,0.00020704848],"domain_scores_gemma":[0.9971706,0.000115075876,0.0003572236,0.00055091624,0.0014576452,0.00034852736],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0063926987,0.00007980171,0.00011936375,0.000084553554,0.0021645946,0.0003193811,0.0009619774,0.000024853263,0.0000019826516],"category_scores_gemma":[0.0030939768,0.000051727144,0.00008782046,0.000048553025,0.00023782668,0.00059092103,0.00012419738,0.00008521052,5.737519e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010626613,0.0001894061,0.18635392,0.0013139565,0.00062868133,0.00001633794,0.00021315408,0.01971667,0.000065982145,0.4367828,0.0029011602,0.35075527],"study_design_scores_gemma":[0.00053444586,0.0000138615505,0.625235,0.000110223365,0.00001389894,0.000021248474,0.000012019438,0.36960745,7.920031e-7,0.0008391438,0.0035682481,0.000043676388],"about_ca_topic_score_codex":0.00068208436,"about_ca_topic_score_gemma":0.029051723,"teacher_disagreement_score":0.69812137,"about_ca_system_score_codex":0.00044395105,"about_ca_system_score_gemma":0.0017004772,"threshold_uncertainty_score":0.9991345},"labels":[],"label_agreement":null},{"id":"W2606573263","doi":"10.23889/ijpds.v1i1.269","title":"PATHS Data Resource: A population-based suite of linkable administrative records and metadata for population health research","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Gini coefficient; Operationalization; Population; Population health; Health equity; Metadata; Equity (law); Health care; Socioeconomic status; Social determinants of health; Geography; Business; Inequality; Environmental health; Medicine; Economic growth; Computer science; Political science; Economic inequality; Economics; World Wide Web","score_opus":0.7370779347199065,"score_gpt":0.6597615478310586,"score_spread":0.0773163868888479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606573263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75585455,0.00081779005,0.049695995,0.08626394,0.016047169,0.012657096,0.0776538,0.0001852805,0.0008243934],"genre_scores_gemma":[0.9466381,0.00010258022,0.03247485,0.0005596653,0.0010189862,0.00006943353,0.018658873,0.000029145796,0.00044835446],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99435914,0.0004960917,0.0016563972,0.000944911,0.0017853228,0.00075814466],"domain_scores_gemma":[0.9907269,0.0017619652,0.0024423013,0.0024129427,0.0022406115,0.0004153205],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.018223539,0.00020095041,0.0004333347,0.000784046,0.009368216,0.0006304603,0.004852421,0.00017608366,0.00005966636],"category_scores_gemma":[0.0155737465,0.0001931818,0.000060469923,0.000318808,0.00033772635,0.006759169,0.0015284569,0.00072281255,0.000004037647],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009421271,0.00024063083,0.8850858,0.00047619882,0.00009023905,0.000002417896,0.001004194,0.00032480276,0.000042215244,0.06980462,0.023055185,0.018931547],"study_design_scores_gemma":[0.00200919,0.00032699088,0.81786984,0.00070391316,0.000038881797,0.000008436575,0.00090406113,0.09947161,0.000005555039,0.013287461,0.06512653,0.00024752857],"about_ca_topic_score_codex":0.013256819,"about_ca_topic_score_gemma":0.009970172,"teacher_disagreement_score":0.19078358,"about_ca_system_score_codex":0.00046474766,"about_ca_system_score_gemma":0.001874753,"threshold_uncertainty_score":0.99331397},"labels":[],"label_agreement":null},{"id":"W2606590435","doi":"10.23889/ijpds.v1i1.28","title":"The Canadian Statistical Demographic Database Research Project: Exploring Potential Use of Administrative Data to Support the Canadian Census Program","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Census; Residence; Population; Linkage (software); Database; Record linkage; Scope (computer science); Geography; Matching (statistics); Computer science; Demography; Statistics; Sociology","score_opus":0.8015763382787666,"score_gpt":0.5945648394228857,"score_spread":0.20701149885588088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606590435","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7116632,0.00004745938,0.027571592,0.072070345,0.02305052,0.012947808,0.15122947,0.00011029149,0.0013092967],"genre_scores_gemma":[0.953775,0.000012337809,0.042293534,0.000048589627,0.0003313951,0.000043324395,0.0033933094,0.000013825194,0.00008868647],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9961869,0.0001500182,0.0006811639,0.00044916256,0.0020034104,0.0005293486],"domain_scores_gemma":[0.9939841,0.0006830735,0.000493826,0.002197677,0.00219756,0.00044375702],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.008885594,0.00012247125,0.0001288762,0.0005492019,0.0069935345,0.0036655867,0.0059118927,0.000043947133,0.000022444587],"category_scores_gemma":[0.021064933,0.000080898026,0.000032399945,0.00033099903,0.0006515974,0.0035868257,0.0008002261,0.00036488625,0.000003992698],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031290264,0.000197175,0.083448365,0.000033313347,0.00018492427,0.0001227567,0.0008318537,0.00033735507,0.00008688147,0.61135775,0.13835186,0.16473489],"study_design_scores_gemma":[0.00047551087,0.00020844745,0.55004424,0.00012155949,0.000058048554,0.0002479345,0.00030222497,0.15183271,0.00002121032,0.01626567,0.2801276,0.00029484252],"about_ca_topic_score_codex":0.605169,"about_ca_topic_score_gemma":0.97793955,"teacher_disagreement_score":0.59509206,"about_ca_system_score_codex":0.00039333364,"about_ca_system_score_gemma":0.0033743088,"threshold_uncertainty_score":0.9994666},"labels":[],"label_agreement":null},{"id":"W2606597455","doi":"10.23889/ijpds.v1i1.387","title":"Midlife and late-life blood pressure and vascular dementia: a population based observational study","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Medicine; Blood pressure; Dementia; Body mass index; Prehypertension; Cohort; Hazard ratio; Population; Stroke (engine); Cohort study; Diabetes mellitus; Internal medicine; Gerontology; Confidence interval; Disease; Environmental health","score_opus":0.1487543846238629,"score_gpt":0.4426758553674638,"score_spread":0.29392147074360087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606597455","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9944579,0.00014653326,0.0015722511,0.0025737623,0.00043873247,0.0006360147,0.000117025236,0.00001257286,0.000045232377],"genre_scores_gemma":[0.9961251,0.000041166863,0.0027598527,0.00028807865,0.00024664964,0.000017531222,0.0004021711,0.000009010879,0.00011044126],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99758375,0.000038934413,0.0003429246,0.00042549722,0.0014079383,0.00020093191],"domain_scores_gemma":[0.998208,0.000064189895,0.00029274455,0.0004163105,0.0007816164,0.00023713901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018646341,0.00011143697,0.00014768812,0.00025740586,0.0010835184,0.000995575,0.00068965415,0.00003301154,0.00007086247],"category_scores_gemma":[0.0021667934,0.00009595704,0.00003495948,0.000075740085,0.00013138987,0.0023542729,0.0004134862,0.00013710215,0.0000012563582],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010266007,0.00023777342,0.9957019,0.00001599544,0.00032889098,0.0000079656365,0.000027003432,0.00002981078,0.00036542682,0.0002753167,0.00007516126,0.0028321147],"study_design_scores_gemma":[0.0031253474,0.00020621455,0.9619108,0.000057646517,0.0005056464,0.00002739864,0.000044857617,0.032833587,0.00002402076,0.00040205105,0.00076949975,0.00009291786],"about_ca_topic_score_codex":0.0003107266,"about_ca_topic_score_gemma":0.00005894548,"teacher_disagreement_score":0.03379107,"about_ca_system_score_codex":0.000020466145,"about_ca_system_score_gemma":0.0002023392,"threshold_uncertainty_score":0.96003526},"labels":[],"label_agreement":null},{"id":"W2606606623","doi":"10.23889/ijpds.v1i1.382","title":"Improving the Accuracy of Length of stay Risk Adjustment Models using Linked Data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Logistic regression; Odds; Angina; Odds ratio; Relative risk; Medical record; Demography; Confidence interval; Myocardial infarction; Surgery","score_opus":0.41473716306113867,"score_gpt":0.5685690171625793,"score_spread":0.15383185410144068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606606623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7885563,0.00046763814,0.17600143,0.0069802282,0.015852228,0.0016061726,0.009968187,0.000024412693,0.0005434347],"genre_scores_gemma":[0.98089486,0.00036810356,0.017212683,0.00045418853,0.00068734493,0.0000040142895,0.00031282633,0.000009139694,0.000056829726],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99748987,0.00011596886,0.0008998911,0.00029408213,0.0009367948,0.00026340102],"domain_scores_gemma":[0.9932281,0.0006812504,0.0030382224,0.0019076974,0.0010590756,0.00008568563],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.005284572,0.00008638383,0.00018420008,0.00015954264,0.002305097,0.00008711328,0.0065275226,0.00004947179,0.000038782284],"category_scores_gemma":[0.0061134947,0.000058189038,0.000039536022,0.00007475483,0.00019843287,0.0052954797,0.0026356278,0.00035447313,0.000001289843],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075808645,0.00026017128,0.49928933,0.00033751642,0.00034075807,0.0000044744725,0.0027944653,0.0060835993,0.0061695254,0.034119435,0.014196526,0.43564612],"study_design_scores_gemma":[0.0010911551,0.00004150404,0.2701297,0.00017667812,0.0000776672,0.000008931543,0.0005047371,0.71709114,0.000050132203,0.0065289014,0.004179881,0.00011955259],"about_ca_topic_score_codex":0.006027458,"about_ca_topic_score_gemma":0.00049009034,"teacher_disagreement_score":0.71100754,"about_ca_system_score_codex":0.000294816,"about_ca_system_score_gemma":0.0017975842,"threshold_uncertainty_score":0.99899375},"labels":[],"label_agreement":null},{"id":"W2606648484","doi":"10.23889/ijpds.v1i1.63","title":"Effects of fetal reduction in multi-fetal pregnancy on perinatal outcomes","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Assisted Reproductive Technology and Twin Pregnancy","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Obstetrics; Fetus; Pregnancy; Odds ratio; Confidence interval; Population; Retrospective cohort study; Twin Pregnancy; Singleton; Live birth; Internal medicine","score_opus":0.0753657091433612,"score_gpt":0.4245033851257291,"score_spread":0.3491376759823679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606648484","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9910262,0.00013976921,0.0028691886,0.0015727138,0.0037532554,0.00042079316,0.00004761509,0.000020555803,0.00014987994],"genre_scores_gemma":[0.9930702,0.00003707672,0.0064030644,0.0000121653475,0.00010142399,0.000009471021,0.00004224777,0.0000068817394,0.000317491],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99865836,0.000014167948,0.00031074727,0.00036539484,0.00050299766,0.00014832585],"domain_scores_gemma":[0.9985727,0.000037501963,0.00042185246,0.0006131984,0.00030444647,0.00005026433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044389072,0.00009350768,0.0001688696,0.00038300635,0.00032999663,0.000065909655,0.0010917329,0.000060613078,0.000007680024],"category_scores_gemma":[0.0032848364,0.00007492254,0.000059198348,0.00008282585,0.0003662147,0.001532236,0.00025974287,0.00022993043,0.000003144147],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003833885,0.00068232184,0.82920015,0.00007435545,0.00010763675,0.000108564745,0.00011246075,0.00004638468,0.016763948,0.0056455145,0.0000418087,0.14683346],"study_design_scores_gemma":[0.0019499514,0.00014036949,0.9870859,0.00072650705,0.000021394771,0.0002834841,0.000022997172,0.0019327616,0.007072186,0.0006251669,0.000065919114,0.000073410956],"about_ca_topic_score_codex":0.000048054964,"about_ca_topic_score_gemma":0.000010151005,"teacher_disagreement_score":0.1578857,"about_ca_system_score_codex":0.00012062879,"about_ca_system_score_gemma":0.00009393731,"threshold_uncertainty_score":0.3932493},"labels":[],"label_agreement":null},{"id":"W2606651138","doi":"10.23889/ijpds.v1i1.383","title":"Policies to Optimize Physician Billing Data in Academic Alternative Relationship Payment Plans: Practices and Perspectives","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"","keywords":"Government (linguistics); Incentive; Payment; Reimbursement; Accountability; Revenue; Business; Corporate governance; Public relations; Family medicine; Medicine; Health care; Accounting; Political science; Finance; Economics","score_opus":0.5133971604535968,"score_gpt":0.49658806627867086,"score_spread":0.016809094174925987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606651138","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7130884,0.00093407714,0.050529942,0.22070505,0.0044026338,0.0011137142,0.006148628,0.00003060926,0.0030469885],"genre_scores_gemma":[0.99131674,0.00051150256,0.0068587866,0.0005986225,0.00050385454,0.000008988762,0.000105484745,0.0000068271165,0.00008918019],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9986066,0.00001611235,0.00047922303,0.00050826144,0.00017684477,0.00021293352],"domain_scores_gemma":[0.9978026,0.00014208864,0.001130144,0.0007132965,0.00010626584,0.00010558619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029696685,0.00008391757,0.00013392698,0.00051507587,0.0006802627,0.0007912223,0.0029101502,0.000030380386,0.0000054227953],"category_scores_gemma":[0.006302002,0.000086667635,0.0000142655545,0.00010839623,0.00010922546,0.005856403,0.0010644279,0.00020358241,0.000011723058],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005216921,0.00004899051,0.30368853,0.000009464655,0.00003396134,0.0000029446044,0.0025970486,0.0017401141,0.000011829186,0.6834486,0.00041834894,0.007947984],"study_design_scores_gemma":[0.0005036608,0.000034884255,0.8325402,0.00009484449,0.000004900614,0.000009771868,0.0010688136,0.081191264,0.0000068049776,0.056734744,0.0276272,0.0001829083],"about_ca_topic_score_codex":0.0070500546,"about_ca_topic_score_gemma":0.00096549967,"teacher_disagreement_score":0.6267139,"about_ca_system_score_codex":0.00020657394,"about_ca_system_score_gemma":0.000056589528,"threshold_uncertainty_score":0.9995621},"labels":[],"label_agreement":null},{"id":"W2606652276","doi":"10.23889/ijpds.v1i1.392","title":"Virtual visits: Friend or foe of patient-centred care?","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medical prescription; Primary care; Medicine; Family medicine; Cohort; Payment; Population; Service (business); Health care; Virtual patient; Medical emergency; Nursing; World Wide Web; Business; Computer science","score_opus":0.10321342854480661,"score_gpt":0.4558814904618052,"score_spread":0.3526680619169986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606652276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881613,0.00012402816,0.0026546249,0.0031663682,0.004478801,0.0005107881,0.0006203623,0.000017661976,0.00026602412],"genre_scores_gemma":[0.9931404,0.000037228205,0.0053889574,0.0002514709,0.0004899239,0.0000036509016,0.0006101151,0.000007533903,0.00007074069],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99797446,0.000010863146,0.0005291054,0.00024610801,0.0010445244,0.00019494607],"domain_scores_gemma":[0.99753183,0.0000500843,0.00073377846,0.00052955764,0.0009889953,0.00016577834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023675476,0.00008182604,0.00014811102,0.0002559881,0.00053842686,0.00016527661,0.0010397853,0.000026289084,0.00013972494],"category_scores_gemma":[0.002006205,0.000061391016,0.000037506972,0.00008725257,0.0001245004,0.0018574029,0.00024352853,0.00009546856,0.0000033288181],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020298616,0.00023984682,0.2746002,0.00006531521,0.00012504528,0.00005577855,0.0047051976,0.000045559642,0.0035770559,0.005696188,0.0077075083,0.70115244],"study_design_scores_gemma":[0.012392532,0.002881785,0.8320135,0.0006311597,0.0002060652,0.00089733914,0.018458247,0.009317664,0.0060756323,0.0009868717,0.115748145,0.00039104934],"about_ca_topic_score_codex":0.00022705508,"about_ca_topic_score_gemma":0.000090158086,"teacher_disagreement_score":0.7007614,"about_ca_system_score_codex":0.0001322282,"about_ca_system_score_gemma":0.00039064372,"threshold_uncertainty_score":0.41411984},"labels":[],"label_agreement":null},{"id":"W2606660084","doi":"10.23889/ijpds.v1i1.283","title":"Linking hospital and immigrant landing data to understand patterns of hospital use among refugees in Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Refugee; Immigration; Demography; Population; Settlement (finance); Geography; Medicine; Sociology; Business","score_opus":0.09713527027243682,"score_gpt":0.4063888825623291,"score_spread":0.30925361228989223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606660084","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9899676,0.000023354492,0.0038098511,0.0010561156,0.0034439103,0.00019901902,0.0014853476,0.0000030682845,0.000011762693],"genre_scores_gemma":[0.9982619,0.000019144238,0.0010165212,0.000063410065,0.00018530643,0.0000018987002,0.0004179157,0.0000063390767,0.00002751485],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99843925,0.00002013063,0.0004154668,0.0003755974,0.0005271701,0.0002224051],"domain_scores_gemma":[0.9984007,0.0000916594,0.00043448806,0.00073495094,0.00019144335,0.00014674815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092789816,0.00008093869,0.00011670855,0.00020338193,0.00037650237,0.0004096076,0.0020673238,0.000026294398,0.000019164514],"category_scores_gemma":[0.00070253987,0.00007475016,0.000011234818,0.00006553231,0.00006404963,0.0028666235,0.00043940305,0.000120930745,5.811176e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003056744,0.000024067684,0.9935855,0.000005087828,0.000012350609,0.000011555766,0.0011349653,0.000023582188,0.0000113678,0.0011216182,0.0003694909,0.003669813],"study_design_scores_gemma":[0.00047610272,0.000052089108,0.99424887,0.00012062881,0.0000053273566,0.000011247176,0.0010787759,0.003023531,0.0000051072416,0.00020234617,0.000685682,0.00009029761],"about_ca_topic_score_codex":0.7091606,"about_ca_topic_score_gemma":0.9030901,"teacher_disagreement_score":0.19392951,"about_ca_system_score_codex":0.00021184208,"about_ca_system_score_gemma":0.0002996564,"threshold_uncertainty_score":0.39498553},"labels":[],"label_agreement":null},{"id":"W2606680228","doi":"10.23889/ijpds.v1i1.379","title":"Impacts of Alternative Billing Claims on Hypertension Prevalence and Mortality Estimates in Alberta, Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"","keywords":"Medicine; Capitation; Salary; Descriptive statistics; Payment; Health care; Family medicine; Demography; Medical emergency; Emergency medicine; Environmental health; Database; Finance; Business","score_opus":0.17717468908925074,"score_gpt":0.3935157057987725,"score_spread":0.21634101670952174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606680228","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9931225,0.00003533854,0.00059376017,0.0041859527,0.0012665088,0.0001274273,0.00041494067,0.0000014525394,0.00025212456],"genre_scores_gemma":[0.99882984,0.00024017376,0.00060197606,0.00019924535,0.000079952566,0.0000020678797,0.000023253582,0.000003483014,0.000020023932],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99902105,0.000005531855,0.00042062116,0.0002562461,0.00015094521,0.00014562569],"domain_scores_gemma":[0.99879277,0.0000901284,0.0005986814,0.00033738452,0.000106242274,0.00007477626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011029093,0.00006152299,0.00012904355,0.00019534618,0.00026308827,0.00017146512,0.0009554489,0.000016822034,0.0000067899714],"category_scores_gemma":[0.0018610475,0.000059271308,0.00001402531,0.000045425237,0.00008355896,0.0012539694,0.00020717521,0.00007216116,0.0000010783974],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019754538,0.000025379872,0.8846826,0.000024317129,0.000015038113,0.0000041333965,0.000066539375,0.0006182025,0.00001375455,0.1119659,0.00007452916,0.0024898662],"study_design_scores_gemma":[0.00024494817,0.000023700453,0.90994877,0.000094776566,0.0000019063887,0.0000063931625,0.000007979508,0.06615319,0.00006079122,0.022555945,0.00083674793,0.00006482654],"about_ca_topic_score_codex":0.8296334,"about_ca_topic_score_gemma":0.48388913,"teacher_disagreement_score":0.34574428,"about_ca_system_score_codex":0.00017820374,"about_ca_system_score_gemma":0.00011008343,"threshold_uncertainty_score":0.52552855},"labels":[],"label_agreement":null},{"id":"W2606710412","doi":"10.23889/ijpds.v1i1.58","title":"Measuring medication adherence: standardized definitions are needed to allow for comparisons","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Medical prescription; Medication adherence; Pharmacy; Logistic regression; Terminology; Confidence interval; Emergency medicine; Internal medicine; Family medicine; Pharmacology","score_opus":0.49157745167292194,"score_gpt":0.48772391317878927,"score_spread":0.003853538494132669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606710412","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14843614,0.00008403572,0.7666249,0.07239508,0.007468629,0.001824462,0.0015080463,0.00008386972,0.0015748129],"genre_scores_gemma":[0.9347752,0.000062566796,0.061620433,0.0016219435,0.0007022013,0.00011190032,0.0005984396,0.000012270459,0.00049507717],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9975792,0.000014455418,0.00048481583,0.00040148606,0.0012725935,0.00024740535],"domain_scores_gemma":[0.9962427,0.00009982738,0.0006935359,0.0008618948,0.0017424946,0.00035954095],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00160436,0.00011194039,0.00020608703,0.000262923,0.0014253941,0.00058372,0.0021241957,0.000043722954,0.00014811658],"category_scores_gemma":[0.0063693384,0.00010108525,0.00007213812,0.00012098484,0.00017588948,0.0014455813,0.0002175086,0.00014496481,0.00006238904],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002394605,0.000681305,0.15345989,0.00012533851,0.00038478881,0.00001880787,0.00046625707,0.00036928698,0.022154078,0.03221375,0.71680075,0.070931114],"study_design_scores_gemma":[0.006784209,0.00036811995,0.68300295,0.0013180086,0.00016946184,0.00025192014,0.0008057559,0.039845105,0.0023447406,0.007521404,0.25712284,0.00046545579],"about_ca_topic_score_codex":0.000120929275,"about_ca_topic_score_gemma":0.000074462405,"teacher_disagreement_score":0.78633904,"about_ca_system_score_codex":0.00019952212,"about_ca_system_score_gemma":0.00050618727,"threshold_uncertainty_score":0.9998746},"labels":[],"label_agreement":null},{"id":"W2606743718","doi":"10.23889/ijpds.v1i1.77","title":"Record Linkage Project Process Model","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Record linkage; Linkage (software); Linked data; Process (computing); Computer science; Session (web analytics); Information retrieval; Data science; World Wide Web; Sociology; Demography; Population","score_opus":0.5924316145985103,"score_gpt":0.6150809603045536,"score_spread":0.022649345706043267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606743718","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17847781,0.000019819594,0.7775746,0.016666738,0.0146773355,0.00091974024,0.0026834363,0.00006785558,0.008912673],"genre_scores_gemma":[0.97147584,0.000028125969,0.024507722,0.0004779174,0.00056180975,0.000010945385,0.00020895104,0.000007956995,0.0027207613],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99495625,0.00003968858,0.0007442303,0.00067537813,0.0033272943,0.00025715627],"domain_scores_gemma":[0.9952112,0.00016721568,0.0011269776,0.0018566457,0.0015191286,0.0001188322],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.01135714,0.000106860374,0.00014635966,0.0005224733,0.0018193842,0.0066603194,0.015555424,0.00003343205,0.000056832905],"category_scores_gemma":[0.017981676,0.00008035814,0.00006165093,0.00021250593,0.00026607353,0.013894221,0.0017894333,0.0001473989,0.000050298782],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024458912,0.0002326289,0.03467113,0.0000126857785,0.00006067905,0.000021246695,0.0006382818,0.0067950366,0.0002689573,0.087668866,0.095427476,0.77395844],"study_design_scores_gemma":[0.0005165318,0.000034982142,0.025744136,0.00004005649,0.000011037892,0.000028771115,0.00025561298,0.708342,0.000046506742,0.17493929,0.08984951,0.0001915207],"about_ca_topic_score_codex":0.00018015908,"about_ca_topic_score_gemma":0.00022470261,"teacher_disagreement_score":0.792998,"about_ca_system_score_codex":0.00008861575,"about_ca_system_score_gemma":0.00033985247,"threshold_uncertainty_score":0.99989796},"labels":[],"label_agreement":null},{"id":"W2606749075","doi":"10.23889/ijpds.v1i1.55","title":"Under-coding of secondary conditions in coded hospital health data: impact of co-existing conditions, death status and number of codes in a record","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Coding (social sciences); Medicine; Logistic regression; Medical record; Diagnosis code; Diabetes mellitus; Obesity; Comorbidity; Hospital discharge; Environmental health; Psychiatry; Statistics; Intensive care medicine; Internal medicine","score_opus":0.4199696901683578,"score_gpt":0.6110085637735188,"score_spread":0.19103887360516097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606749075","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98875,0.00002298814,0.0020911098,0.00084346806,0.00075598387,0.00038011477,0.006706269,0.0000050132353,0.00044509454],"genre_scores_gemma":[0.9943415,0.00024153761,0.0030303546,0.00008071739,0.00007539675,0.0000064572323,0.0022072252,0.000005105572,0.000011712133],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99740165,0.000118213604,0.0014369178,0.00021024392,0.00053777354,0.00029520338],"domain_scores_gemma":[0.99600166,0.0005521266,0.002329419,0.00046593157,0.0004906395,0.00016020543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045318576,0.00008185433,0.00029352872,0.00040138335,0.0007400236,0.000044890563,0.0010075208,0.000059235754,0.00010241783],"category_scores_gemma":[0.0039144955,0.00007382517,0.000024958073,0.00012713709,0.00025145576,0.0028470254,0.00033284782,0.00037136205,0.0000011922709],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006216452,0.000057751935,0.9830285,0.00015973495,0.000012772963,5.892712e-7,0.0007373107,0.000076473814,0.000071630624,0.0129047,0.0006139328,0.0022744637],"study_design_scores_gemma":[0.0013190774,0.00008618374,0.9696834,0.001124416,0.000004307571,0.0000071358195,0.0010301098,0.02177895,0.0000067771402,0.0047853654,0.00011237934,0.00006188936],"about_ca_topic_score_codex":0.008862578,"about_ca_topic_score_gemma":0.0016224863,"teacher_disagreement_score":0.021702478,"about_ca_system_score_codex":0.00035524077,"about_ca_system_score_gemma":0.0017879884,"threshold_uncertainty_score":0.99773747},"labels":[],"label_agreement":null},{"id":"W2606759006","doi":"10.23889/ijpds.v1i1.306","title":"Linked Data Paves the Way to Improved Health Care","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Health care; Population; Business; Payment; Variety (cybernetics); Presentation (obstetrics); Medicine; Medical emergency; Computer science; Finance; Environmental health; Political science","score_opus":0.2693066539758271,"score_gpt":0.5815121018255263,"score_spread":0.31220544784969917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606759006","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07212426,0.00078464847,0.026280135,0.8187166,0.06146845,0.0042061727,0.01248699,0.00014478879,0.003787985],"genre_scores_gemma":[0.9288606,0.0002542628,0.015048887,0.047237255,0.0044348086,0.000042295513,0.002827349,0.000026886231,0.0012676404],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99727434,0.000112293514,0.0007273302,0.00050590927,0.0008644538,0.00051568175],"domain_scores_gemma":[0.9947297,0.00030487476,0.00094400614,0.0027466728,0.0009721952,0.00030253202],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0045272284,0.000116759344,0.00018364053,0.00017619577,0.008249723,0.0005021848,0.01120204,0.00005291193,0.00007798051],"category_scores_gemma":[0.004116326,0.00007752825,0.000034675413,0.00010030711,0.00013203564,0.003422306,0.0036571915,0.00045717077,0.000052589625],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028345227,0.000050031686,0.12661059,0.0001003864,0.00006755496,0.000005484514,0.004693846,0.000026270332,0.00029322464,0.013671904,0.49059352,0.36360374],"study_design_scores_gemma":[0.0005731717,0.000052809486,0.44298196,0.00007876894,0.000008266124,0.0000094542675,0.0009621571,0.0026144823,0.0000022088752,0.00088369724,0.5517199,0.00011310735],"about_ca_topic_score_codex":0.0029156094,"about_ca_topic_score_gemma":0.0051854486,"teacher_disagreement_score":0.85673636,"about_ca_system_score_codex":0.0007692752,"about_ca_system_score_gemma":0.0024611605,"threshold_uncertainty_score":0.99414784},"labels":[],"label_agreement":null},{"id":"W2606772694","doi":"10.23889/ijpds.v1i1.307","title":"Information Management at a Health Services Research Organization in Toronto, Ontario, Canada: Moving from Identifiable Data to Coded Data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Identifier; Computer science; Population; Confidentiality; Data sharing; Data quality; Data collection; Business; Data science; Internet privacy; Knowledge management; Computer security; Medicine; Environmental health; Service (business)","score_opus":0.3377112444792492,"score_gpt":0.528678948045083,"score_spread":0.19096770356583376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606772694","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5165605,0.00021807523,0.30161253,0.052608274,0.035612047,0.0054004956,0.08231876,0.00009836282,0.005570969],"genre_scores_gemma":[0.9311269,0.0000890073,0.02059636,0.0018421513,0.0003164405,0.000008774106,0.04438577,0.000012420197,0.0016221558],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9918384,0.00014132679,0.0012234141,0.0008795239,0.0054964568,0.00042086904],"domain_scores_gemma":[0.99086004,0.0002631424,0.001014975,0.0060089505,0.0015982949,0.00025459903],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.01983506,0.0001229078,0.00019521076,0.00049183227,0.00222174,0.007076413,0.030902933,0.000029627883,0.0006054833],"category_scores_gemma":[0.004844438,0.00011203123,0.000009615434,0.00056703924,0.00008294446,0.038020194,0.024607388,0.00015765599,0.00006315676],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029608712,0.00019170756,0.16428673,0.000047756996,0.0001276171,0.000028226788,0.0042305524,0.0027122933,0.000102261656,0.013885882,0.56244814,0.25164273],"study_design_scores_gemma":[0.0005180527,0.000014133216,0.60067356,0.00014128746,0.000006532882,0.0000056620324,0.0037294847,0.053326786,0.000009082264,0.0021443276,0.33928314,0.00014792186],"about_ca_topic_score_codex":0.9797177,"about_ca_topic_score_gemma":0.9981719,"teacher_disagreement_score":0.43638685,"about_ca_system_score_codex":0.003999388,"about_ca_system_score_gemma":0.001340077,"threshold_uncertainty_score":0.9998241},"labels":[],"label_agreement":null},{"id":"W2606781361","doi":"10.23889/ijpds.v1i1.274","title":"Gaps in Health and Wealth: The relationship between trends in income inequality and breastfeeding inequalities","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Breastfeeding Practices and Influences","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Breastfeeding; Inequality; Gini coefficient; Demography; Socioeconomic status; Population; Economic inequality; Residence; Household income; Medicine; Geography; Environmental health; Pediatrics; Mathematics; Sociology","score_opus":0.2511889592891803,"score_gpt":0.4912116816509348,"score_spread":0.24002272236175454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606781361","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9105499,0.00014978711,0.000106964144,0.08852879,0.00038848814,0.00010012926,0.00007641303,0.0000051798243,0.00009437474],"genre_scores_gemma":[0.9983429,0.000092843984,0.00087599485,0.0002762258,0.0002877521,0.0000029469356,0.00006713926,0.0000041093263,0.000050110175],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99847597,0.000059468992,0.0005361539,0.0002424277,0.00050372904,0.0001822761],"domain_scores_gemma":[0.99836475,0.00047719892,0.000599089,0.000286597,0.00013048941,0.00014186869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005635009,0.00007558722,0.00015546722,0.00045389173,0.0007069036,0.000585563,0.00064926746,0.00003217113,0.0000055808855],"category_scores_gemma":[0.0045594815,0.000054245862,0.000014349858,0.00016689833,0.0002561584,0.0035569738,0.00030224293,0.00028587203,3.208094e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052217383,0.000010088579,0.94411737,0.0000174051,0.0000039948995,0.0000012230818,0.00037872163,0.00000468432,0.000004253862,0.007260238,0.000022930904,0.048126902],"study_design_scores_gemma":[0.0007035633,0.00005534694,0.9919723,0.0003064875,0.0000044799826,0.00014625574,0.00023029232,0.0018849466,7.286064e-7,0.0041355314,0.0005052702,0.00005478358],"about_ca_topic_score_codex":0.004428959,"about_ca_topic_score_gemma":0.0007048057,"teacher_disagreement_score":0.08825257,"about_ca_system_score_codex":0.0001271295,"about_ca_system_score_gemma":0.00015277359,"threshold_uncertainty_score":0.6695291},"labels":[],"label_agreement":null},{"id":"W2606808438","doi":"10.23889/ijpds.v1i1.49","title":"Record Linkage Methodology for the Social Data Linkage Environment at Statistics Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Record linkage; Probabilistic logic; Linkage (software); Statistic; Computer science; Population; Data science; Data mining; Statistics; Artificial intelligence; Mathematics","score_opus":0.6885121311704627,"score_gpt":0.5782337375018265,"score_spread":0.11027839366863623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606808438","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031240406,0.000027882998,0.92535585,0.023205759,0.009652668,0.00041308563,0.03812001,0.0000062683257,0.00009443123],"genre_scores_gemma":[0.399483,0.00046808666,0.55940354,0.005472804,0.005795038,0.000060524882,0.017749289,0.00004483543,0.011522882],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9953352,0.00016206737,0.0008274852,0.00074036804,0.0026291832,0.00030567244],"domain_scores_gemma":[0.99225146,0.0031266932,0.0013314175,0.0026756476,0.00049859745,0.000116216885],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.019863296,0.000120445045,0.00018587998,0.00013126784,0.004261568,0.0022066596,0.019788513,0.00003855733,0.00023214993],"category_scores_gemma":[0.024552397,0.0000822382,0.000037983868,0.000081620456,0.0004185512,0.0031026592,0.0062759416,0.00015298424,0.000018124456],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011556269,0.000033225042,0.0038829206,0.0000039217734,0.00007218737,0.000008347694,0.00010987888,0.00027363273,0.00007185533,0.02878278,0.5398387,0.42680702],"study_design_scores_gemma":[0.00039825268,0.000021301457,0.07674168,0.0000058496103,0.00003194342,0.00001401387,0.00022185966,0.061006244,0.0000136218505,0.020937415,0.84048766,0.000120177014],"about_ca_topic_score_codex":0.039649785,"about_ca_topic_score_gemma":0.24440314,"teacher_disagreement_score":0.42668682,"about_ca_system_score_codex":0.00032949806,"about_ca_system_score_gemma":0.00042749342,"threshold_uncertainty_score":0.9988291},"labels":[],"label_agreement":null},{"id":"W2606808455","doi":"10.23889/ijpds.v1i1.79","title":"An Integrated Genomics and Clinical Resource for Data-Driven Health Services Policy and Practice Decisionmaking","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"BRCA gene mutations in cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Health care; Medicine; Breast cancer; Biobank; Family medicine; Cancer; Gerontology; Internal medicine; Bioinformatics; Biology","score_opus":0.13527359070407935,"score_gpt":0.5334549334104957,"score_spread":0.3981813427064163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606808455","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6798701,0.0006116264,0.296411,0.01543464,0.0025979204,0.00076294685,0.004208241,0.000015299414,0.000088162175],"genre_scores_gemma":[0.7851693,0.00067541486,0.20835458,0.0014356587,0.001452086,0.00000431582,0.002865633,0.000014235506,0.00002877841],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986359,0.000055133107,0.00036934792,0.0005293181,0.00026000425,0.00015031928],"domain_scores_gemma":[0.9976024,0.00013790636,0.0006407034,0.0009736185,0.00050766504,0.00013768676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031770093,0.00007976889,0.000092875845,0.000103683116,0.0009451452,0.0009845351,0.0024758917,0.00005079576,0.0000010010117],"category_scores_gemma":[0.0041577606,0.00007348105,0.000016684957,0.000039211394,0.00021797785,0.0004338231,0.0009905361,0.00007994589,2.5335922e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011155254,0.00015003061,0.03392078,0.000024783667,0.00019629768,0.0000025036247,0.00030952087,0.0013030806,0.006458749,0.002741032,0.004048444,0.94972926],"study_design_scores_gemma":[0.0013179544,0.00031957924,0.070224784,0.00007122817,0.000033336863,0.0003721163,0.00050189474,0.24107637,0.00010181215,0.0010150055,0.6847654,0.00020052564],"about_ca_topic_score_codex":0.00028953972,"about_ca_topic_score_gemma":0.00049422623,"teacher_disagreement_score":0.94952875,"about_ca_system_score_codex":0.00009650575,"about_ca_system_score_gemma":0.0006627954,"threshold_uncertainty_score":0.94938946},"labels":[],"label_agreement":null},{"id":"W2606810975","doi":"10.23889/ijpds.v1i1.364","title":"Big Data, Big Responsibility! Building best-practice privacy strategies into a large-scale neuroinformatics platform","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ontario Brain Institute","funders":"","keywords":"Neuroinformatics; Computer science; Data sharing; Big data; Data science; Health informatics; Data governance; Informatics; Variety (cybernetics); Best practice; Analytics; Computer security; Health care; Medicine; Engineering; Data mining; Political science; Artificial intelligence","score_opus":0.13559272408265607,"score_gpt":0.42734358436257497,"score_spread":0.2917508602799189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606810975","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7979256,0.000019755182,0.18980522,0.0042996486,0.004407395,0.00057119055,0.00069384655,0.00003635581,0.0022410136],"genre_scores_gemma":[0.9253259,0.00011895152,0.072920986,0.0006187819,0.00058741233,0.000006295215,0.0003110825,0.000018946119,0.000091695845],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99581504,0.00007093343,0.00077114056,0.00087954116,0.0019261076,0.00053724326],"domain_scores_gemma":[0.9953455,0.00038027912,0.0011067123,0.002715535,0.0001534005,0.0002985947],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.007537019,0.00020099261,0.0001697032,0.00021620444,0.002752228,0.0024405436,0.007983837,0.00006292655,0.000088696186],"category_scores_gemma":[0.011211507,0.0001891784,0.00004162278,0.00018976325,0.0005648396,0.025581244,0.005730155,0.0004257262,0.00011752892],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005798072,0.00076653284,0.12191359,0.000046424066,0.00008151111,0.000088986824,0.004003596,0.0063785785,0.008997769,0.0033220702,0.0022885911,0.8515325],"study_design_scores_gemma":[0.0017337064,0.00021174616,0.2921949,0.00018035514,0.000074423326,0.00049950386,0.0031176002,0.39437735,0.00034534073,0.014391616,0.29219985,0.00067361724],"about_ca_topic_score_codex":0.0011356892,"about_ca_topic_score_gemma":0.0008511676,"teacher_disagreement_score":0.8508589,"about_ca_system_score_codex":0.000578273,"about_ca_system_score_gemma":0.00029640627,"threshold_uncertainty_score":0.998595},"labels":[],"label_agreement":null},{"id":"W2606823425","doi":"10.23889/ijpds.v1i1.376","title":"Social Housing and Health in Manitoba","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; University of Manitoba; Manitoba Health","funders":"","keywords":"Residence; Confounding; Population; Demography; Gerontology; Public housing; Social determinants of health; Environmental health; Medicine; Psychology; Public health; Sociology; Economics; Economic growth","score_opus":0.29960182719575895,"score_gpt":0.5437632605113162,"score_spread":0.24416143331555723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606823425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66554755,0.00013049637,0.0016529209,0.32363927,0.0069717597,0.00038486268,0.00015121685,0.000023404242,0.0014985028],"genre_scores_gemma":[0.9960466,0.00022272987,0.001405979,0.0013792203,0.0008716972,0.0000013166818,0.000018356337,0.0000030794788,0.000051045023],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99879664,0.000029662935,0.00023512705,0.00016993503,0.00050298765,0.00026563936],"domain_scores_gemma":[0.999255,0.00003923895,0.0002861811,0.00014428451,0.0001527093,0.00012259655],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0037226698,0.00004136798,0.00008126112,0.00013739939,0.0040280763,0.0013016372,0.001383244,0.00002336242,0.000008728595],"category_scores_gemma":[0.0009943917,0.00004061828,0.0000144758105,0.000053530926,0.00026930103,0.0029213922,0.00022847154,0.00009028379,0.0000010328001],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012284563,0.000017904727,0.704787,0.0000066535417,0.0000033844372,0.0000026194832,0.0012881715,0.0000060078346,0.000001587897,0.1294211,0.0023093952,0.16214389],"study_design_scores_gemma":[0.00023260436,0.0000049471555,0.9499719,0.000035261048,8.181765e-7,0.0000034352463,0.0007392853,0.0008102071,3.5535103e-7,0.007928657,0.040223412,0.000049120757],"about_ca_topic_score_codex":0.03373557,"about_ca_topic_score_gemma":0.072804235,"teacher_disagreement_score":0.33049902,"about_ca_system_score_codex":0.00033111044,"about_ca_system_score_gemma":0.00046749573,"threshold_uncertainty_score":0.9997351},"labels":[],"label_agreement":null},{"id":"W2606832062","doi":"10.23889/ijpds.v1i1.73","title":"Do socially complex patients seek primary care from clinics specifically designed to meet their needs?","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health","funders":"","keywords":"Primary care; Medicine; Family medicine; Social Welfare; Population; Health care; Cohort; Service (business); Nursing; Business; Environmental health; Political science","score_opus":0.260851714209445,"score_gpt":0.52212246374129,"score_spread":0.26127074953184504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606832062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87816566,0.000108836175,0.024235722,0.029728493,0.03442974,0.0026297083,0.014856253,0.00012312789,0.015722478],"genre_scores_gemma":[0.94838756,0.00007524122,0.028854078,0.016037213,0.0028205917,0.000025901609,0.0035020078,0.000030692147,0.0002667386],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966172,0.00014149312,0.0010121249,0.0004714742,0.0012560894,0.0005015976],"domain_scores_gemma":[0.9947271,0.00053281285,0.0011064189,0.0010220374,0.0022399898,0.0003716809],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00180675,0.00017321645,0.0003009188,0.0003112534,0.004485209,0.0005386046,0.0048786923,0.000114542294,0.00020952674],"category_scores_gemma":[0.00205104,0.00014546339,0.00008873792,0.00013233701,0.00014005353,0.0024729916,0.0014242859,0.00031971183,0.00007009031],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053303596,0.000096027885,0.80591553,0.00003625072,0.000053854048,0.0000063292523,0.0031830403,0.000022407865,0.0003984475,0.007507399,0.08345662,0.09879105],"study_design_scores_gemma":[0.0012221748,0.00007083696,0.8844287,0.00009280005,0.000013205108,9.59938e-7,0.00066322106,0.00016043361,0.0000033887288,0.0048846174,0.10829132,0.00016834827],"about_ca_topic_score_codex":0.00040430462,"about_ca_topic_score_gemma":0.00085159764,"teacher_disagreement_score":0.0986227,"about_ca_system_score_codex":0.0014047209,"about_ca_system_score_gemma":0.002490562,"threshold_uncertainty_score":0.9968108},"labels":[],"label_agreement":null},{"id":"W2606854604","doi":"10.23889/ijpds.v1i1.118","title":"Multiple Correspondence Analysis is a Useful Tool to Visualize Complex Categorical Correlated Data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Saskatchewan Health Quality Council","funders":"","keywords":"Categorical variable; Confounding; Covariate; Medicine; Correspondence analysis; Population; Schizophrenia (object-oriented programming); Multiple correspondence analysis; Psychiatry; Statistics; Environmental health; Mathematics; Internal medicine","score_opus":0.33774371209896364,"score_gpt":0.48852830735674724,"score_spread":0.1507845952577836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606854604","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90540916,0.000012853576,0.07818555,0.007461178,0.002197733,0.00028061745,0.0063177855,0.000034741217,0.00010041262],"genre_scores_gemma":[0.9794875,0.000014673753,0.017022206,0.000717567,0.00042585115,0.0000032789642,0.0018083865,0.0000013474018,0.00051919546],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99687684,0.000093807284,0.00056436873,0.0008111765,0.0013130452,0.00034078563],"domain_scores_gemma":[0.99672496,0.00082771917,0.00055565516,0.00078670273,0.0008273561,0.00027762915],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0029773572,0.0001448928,0.0002739244,0.00013256421,0.001609048,0.001993501,0.0075747734,0.000060737333,0.0010002332],"category_scores_gemma":[0.011974911,0.00006889206,0.00010533415,0.000699236,0.000129847,0.0022208327,0.0015632268,0.0001629907,0.000049455157],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005560558,0.00024713148,0.70873773,0.0000025131715,0.00059457286,0.00004520349,0.00008883766,0.0007562792,0.029316349,0.002612054,0.027231155,0.22981212],"study_design_scores_gemma":[0.00014317212,0.00004371208,0.64581037,0.000005744601,0.000118089,0.000018033068,0.000026435226,0.30964583,0.00004680564,0.000526462,0.04346777,0.00014756361],"about_ca_topic_score_codex":0.0012502172,"about_ca_topic_score_gemma":0.0009876767,"teacher_disagreement_score":0.30888954,"about_ca_system_score_codex":0.00011952273,"about_ca_system_score_gemma":0.000036093392,"threshold_uncertainty_score":0.999913},"labels":[],"label_agreement":null},{"id":"W2606898351","doi":"10.23889/ijpds.v1i1.24","title":"Effect of an Intensive Multi-Modal Intervention for Attention-Deficit Hyperactivity Disorder (ADHD) on Equity in Children’s Health and Educational Outcomes","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Attention Deficit Hyperactivity Disorder","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Medicine; Attention deficit hyperactivity disorder; Rate ratio; Emergency department; Intervention (counseling); Medical prescription; Socioeconomic status; Population; Pediatrics; Psychiatry; Demography; Environmental health; Nursing","score_opus":0.10732577800589964,"score_gpt":0.5148972470410518,"score_spread":0.4075714690351521,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606898351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98757017,0.00003472015,0.0048206686,0.004975765,0.0011360302,0.0009852222,0.00045927466,0.000009092748,0.000009065537],"genre_scores_gemma":[0.9961167,0.000019091756,0.002338691,0.00011853248,0.00015929875,0.0000379058,0.0011027537,0.000015862615,0.00009118969],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99788797,0.000085679174,0.0005610273,0.0005062587,0.00072282745,0.00023624222],"domain_scores_gemma":[0.99723494,0.00028973882,0.0009056116,0.0005551973,0.00084408955,0.00017045073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002361239,0.00016645141,0.000344513,0.00047126866,0.0005781937,0.00028483264,0.00079316844,0.000053570424,0.000017617966],"category_scores_gemma":[0.0076815877,0.00014180448,0.00012595656,0.00007894512,0.00020896086,0.0030159603,0.00032754542,0.00021694305,0.0000019160418],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057523506,0.00057300413,0.94483125,0.000042218908,0.00005549208,5.0791954e-7,0.000037605936,0.00007527662,0.0003283852,0.0005411313,0.000016445163,0.05292347],"study_design_scores_gemma":[0.005175808,0.00081006315,0.9728378,0.00022680739,0.000032278018,0.00011311922,0.00021746288,0.020213986,0.000016736187,0.0002188332,0.000021752443,0.00011532847],"about_ca_topic_score_codex":0.00086216844,"about_ca_topic_score_gemma":0.00029639946,"teacher_disagreement_score":0.052808143,"about_ca_system_score_codex":0.00026824386,"about_ca_system_score_gemma":0.00022687751,"threshold_uncertainty_score":0.9196133},"labels":[],"label_agreement":null},{"id":"W2606901347","doi":"10.23889/ijpds.v1i1.72","title":"Comparison of Risk Adjustment Methods in Patients with Liver Disease Using Electronic Medical Record","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Akaike information criterion; Medicine; Cohort; Cirrhosis; Liver disease; Logistic regression; Statistic; Internal medicine; Medical record; Emergency medicine; Statistics; Mathematics","score_opus":0.1615232314019049,"score_gpt":0.4700567759527047,"score_spread":0.3085335445507998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606901347","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94951636,0.00020041749,0.047627077,0.0001807985,0.0018917078,0.00017525649,0.0003665223,0.000002589414,0.000039304676],"genre_scores_gemma":[0.98743784,0.000089000954,0.012235103,0.000018918789,0.00014326151,0.000001963163,0.00005928705,0.000005567876,0.000009055789],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985934,0.000021926026,0.00067480904,0.0002492404,0.00026949073,0.00019116912],"domain_scores_gemma":[0.9980014,0.000025129744,0.0012600167,0.00037890457,0.0001936206,0.00014091434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026466746,0.000063494095,0.00019103967,0.00026378885,0.00028458406,0.00012233172,0.0012936468,0.000032995475,0.00004062853],"category_scores_gemma":[0.001532992,0.000048929902,0.00003109072,0.0000763853,0.00009219831,0.0013741268,0.0001810121,0.00015532087,0.0000021750102],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056512366,0.00007114565,0.94242036,0.0000055563164,0.000011455479,4.751708e-7,0.000043481075,0.00015117938,4.5678152e-7,0.006034116,0.000008065347,0.051197223],"study_design_scores_gemma":[0.00053757284,0.000043150143,0.9034695,0.00006365878,0.0000019883255,0.0000012897939,0.000011154822,0.092484534,0.0000015777532,0.0024925948,0.0008310141,0.00006193227],"about_ca_topic_score_codex":0.005040202,"about_ca_topic_score_gemma":0.0006551311,"teacher_disagreement_score":0.092333354,"about_ca_system_score_codex":0.0003091391,"about_ca_system_score_gemma":0.00018475117,"threshold_uncertainty_score":0.7619311},"labels":[],"label_agreement":null},{"id":"W2606917412","doi":"10.23889/ijpds.v1i1.389","title":"Methodological research priorities for data sciences: Report from The International Methodology Consortium for Coded Health Information (IMECCHI)","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Health care; Big data; Data science; Data quality; Quality (philosophy); Thematic analysis; Computer science; Population health; Knowledge management; Data mining; Engineering; Qualitative research; Political science; Operations management","score_opus":0.9649618177352858,"score_gpt":0.746948965823359,"score_spread":0.21801285191192676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606917412","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0068831444,0.00006850558,0.8396384,0.12431312,0.019784888,0.0024932122,0.006183869,0.00004690429,0.0005879388],"genre_scores_gemma":[0.128014,0.0004398369,0.8337615,0.012780762,0.0074111125,0.00050046755,0.016512338,0.000023942917,0.0005560018],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99384934,0.0007825411,0.0019371363,0.0005862598,0.0021018104,0.00074292574],"domain_scores_gemma":[0.9758691,0.01552679,0.0029291576,0.0017130504,0.003687125,0.00027475687],"candidate_categories":["metaresearch","sts","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.103559405,0.00014478702,0.0003289542,0.00037080882,0.012811951,0.0010187684,0.0101588955,0.0001562634,0.00009000909],"category_scores_gemma":[0.1714339,0.000099378885,0.000066171466,0.0001573309,0.00097208476,0.0073291142,0.002178801,0.000740521,0.000015043516],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001885613,0.0000725372,0.063838646,0.00020605701,0.00015832335,0.0000028199681,0.003609345,0.00018643422,0.00012532908,0.20577979,0.5206168,0.20351826],"study_design_scores_gemma":[0.0018367841,0.00016989777,0.057537563,0.00029266722,0.000018518931,0.0000530784,0.0020971901,0.20205909,0.000014692998,0.055225324,0.68052983,0.00016536063],"about_ca_topic_score_codex":0.002656997,"about_ca_topic_score_gemma":0.00067405734,"teacher_disagreement_score":0.2033529,"about_ca_system_score_codex":0.00047994975,"about_ca_system_score_gemma":0.0039084773,"threshold_uncertainty_score":0.99519664},"labels":[],"label_agreement":null},{"id":"W2606985552","doi":"10.23889/ijpds.v1i1.105","title":"Predicting who applies to Public Housing using Linked Administrative Data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"","keywords":"Population; Public health; Census; Receipt; Medicine; Environmental health; Cohort; Health care; Gerontology; Business; Economic growth; Economics; Nursing","score_opus":0.45662308277918306,"score_gpt":0.5553332303785166,"score_spread":0.0987101475993335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606985552","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87543744,0.000054309876,0.046796855,0.059224833,0.012794075,0.0008741562,0.0019955616,0.00007307629,0.0027496805],"genre_scores_gemma":[0.98122925,0.000039010996,0.01568328,0.0007385454,0.0020130242,0.0000030830133,0.00014660213,0.000008160308,0.00013905042],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973775,0.00004813186,0.0004095476,0.0004319317,0.0012848433,0.00044800463],"domain_scores_gemma":[0.9973579,0.0001755067,0.00053451624,0.0008865451,0.0006793522,0.00036614898],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.004620528,0.00008991024,0.00013056184,0.00020382387,0.0065436703,0.0045845946,0.006958014,0.00004574241,0.000035243287],"category_scores_gemma":[0.011017005,0.00008616015,0.000025572526,0.00014727701,0.00036355027,0.009308134,0.0014468449,0.00015063635,0.000003904747],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000484256,0.000047925783,0.87246704,0.000014382119,0.000040099538,0.000008920615,0.002329459,0.0002058101,0.00006336558,0.07320553,0.0023399524,0.049229067],"study_design_scores_gemma":[0.0005942544,0.00003650225,0.6758496,0.0003241538,0.000026377063,0.000026600663,0.0054261996,0.1126756,0.000015692758,0.0041635595,0.20047344,0.000388012],"about_ca_topic_score_codex":0.0070901387,"about_ca_topic_score_gemma":0.010575985,"teacher_disagreement_score":0.19813348,"about_ca_system_score_codex":0.0003217713,"about_ca_system_score_gemma":0.0012562368,"threshold_uncertainty_score":0.99952173},"labels":[],"label_agreement":null},{"id":"W2606993211","doi":"10.23889/ijpds.v1i1.167","title":"Measuring cumulative anticholinergic medicines burden in older Australian women","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Anticholinergic; Medicine; Drug; Longitudinal study; Anticholinergic agents; Psychiatry; Internal medicine","score_opus":0.39974294465147875,"score_gpt":0.5330232602304313,"score_spread":0.1332803155789526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606993211","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98246026,0.00002075493,0.00026780108,0.014146184,0.0023235844,0.0002474533,0.000038543047,0.00000968285,0.0004857575],"genre_scores_gemma":[0.9972726,0.000041781263,0.0010678482,0.00035808876,0.0007370752,0.0000044981725,0.0000563045,0.000007020254,0.00045474418],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980948,0.000019031737,0.00038937034,0.00027422787,0.0009612378,0.00026133287],"domain_scores_gemma":[0.9985141,0.00007748932,0.00038898646,0.00041604537,0.0003894268,0.00021390789],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017683669,0.00009215277,0.00015777885,0.0002874439,0.00039666914,0.0003651482,0.0012721069,0.000030802985,0.0000916798],"category_scores_gemma":[0.0034369717,0.00007168316,0.00003273816,0.000096725504,0.00016129471,0.0033948866,0.00026241547,0.00022951164,0.00000776206],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005198006,0.00014399845,0.97393584,0.0000305683,0.000073612304,0.000079168145,0.00079900067,0.0004943095,0.003972207,0.0008365833,0.0005766164,0.018538287],"study_design_scores_gemma":[0.0027556245,0.0000543571,0.9281625,0.0002669747,0.000026107371,0.00014987674,0.00019917215,0.054620314,0.00019951822,0.00081912876,0.012629122,0.00011726079],"about_ca_topic_score_codex":0.0002109569,"about_ca_topic_score_gemma":0.00002503435,"teacher_disagreement_score":0.054126006,"about_ca_system_score_codex":0.00022154364,"about_ca_system_score_gemma":0.00011964001,"threshold_uncertainty_score":0.41146246},"labels":[],"label_agreement":null},{"id":"W2607070476","doi":"10.23889/ijpds.v1i1.213","title":"Conducting Population Health Intervention Research using Linked Databases: An Evaluation of Home Visiting Programs for At-Risk Families","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child Abuse and Trauma","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"","keywords":"Medicine; Relative risk; Intervention (counseling); Welfare; Population; Confidence interval; Health care; Foster care; Family medicine; Demography; Gerontology; Environmental health; Nursing","score_opus":0.6826403867971393,"score_gpt":0.6182507063874668,"score_spread":0.06438968040967252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607070476","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98333377,0.000103698345,0.011583573,0.00024316223,0.003053603,0.0010041441,0.00061635335,0.000017936994,0.0000437804],"genre_scores_gemma":[0.98408425,0.000016660391,0.011981204,0.000018058876,0.0008487802,0.00002783527,0.0029833538,0.000018177761,0.000021693457],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99612427,0.00036410792,0.0008535859,0.0005883832,0.0016975427,0.00037209186],"domain_scores_gemma":[0.99451584,0.00019382764,0.0018333619,0.0009202468,0.0024143455,0.00012238952],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.021635812,0.00011834602,0.00019004554,0.0005859663,0.0027014373,0.000608602,0.0017294677,0.00004722597,0.000063051106],"category_scores_gemma":[0.0028505425,0.00011556514,0.00008412034,0.00017991924,0.00021595118,0.0046306127,0.00038514647,0.00022116426,0.0000027200315],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037393055,0.0003221061,0.3647888,0.000034017532,0.00010343102,9.024687e-7,0.0014537903,0.00082940323,0.0009858152,0.007965941,0.00013371745,0.62300813],"study_design_scores_gemma":[0.002907795,0.0002584279,0.7746773,0.00042970607,0.0000668514,0.00006746475,0.0020914066,0.21312843,0.000106022795,0.0056821303,0.00040167125,0.00018282232],"about_ca_topic_score_codex":0.007432904,"about_ca_topic_score_gemma":0.0019959076,"teacher_disagreement_score":0.6228253,"about_ca_system_score_codex":0.0005323332,"about_ca_system_score_gemma":0.00017703285,"threshold_uncertainty_score":0.9991767},"labels":[],"label_agreement":null},{"id":"W2607088927","doi":"10.23889/ijpds.v1i1.69","title":"ICD-11: towards better capture of quality and safety events in hospital","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Quality (philosophy); ICD-10; Quality management; Patient safety; Computer science; Coding (social sciences); Health care; Medicine; Data science; Medical emergency; Operations management; Engineering; Nursing","score_opus":0.3500842049148295,"score_gpt":0.5740981480393901,"score_spread":0.22401394312456058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607088927","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9575544,0.000013979535,0.0063931467,0.030520674,0.0042919293,0.0003465363,0.00034393332,0.000007345449,0.0005280315],"genre_scores_gemma":[0.9960885,0.000045733595,0.0025808315,0.0007319907,0.0003078432,0.000005593455,0.00014902036,0.0000032123282,0.00008725445],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979703,0.00007097454,0.0008210931,0.00016756242,0.0007609436,0.00020917221],"domain_scores_gemma":[0.99793863,0.00013067626,0.0009698301,0.00034697383,0.00048440442,0.00012950078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052429987,0.00006089927,0.00013839242,0.00016832098,0.0010861813,0.00004127584,0.0011617212,0.00007024306,0.000050949813],"category_scores_gemma":[0.0048501,0.000049118713,0.00001910469,0.00005215501,0.00012074587,0.002206815,0.00038742422,0.00029109407,0.0000035832463],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000076860124,0.000028739354,0.97361994,0.00006121806,0.0000048539473,5.778818e-7,0.0008828144,0.000010355309,0.000023733226,0.0062631355,0.00093868404,0.018089088],"study_design_scores_gemma":[0.00082766684,0.000020253676,0.98501545,0.0002257007,0.0000024631966,0.0000024906515,0.0001897299,0.0053046616,0.000002717704,0.003169713,0.00518458,0.000054572545],"about_ca_topic_score_codex":0.0019527517,"about_ca_topic_score_gemma":0.00051912945,"teacher_disagreement_score":0.038534097,"about_ca_system_score_codex":0.00016215614,"about_ca_system_score_gemma":0.00033148468,"threshold_uncertainty_score":0.8354138},"labels":[],"label_agreement":null},{"id":"W2607131258","doi":"10.23889/ijpds.v1i1.57","title":"Methods of defining hypertension in electronic medical records: validation against national survey data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Blood Pressure and Hypertension Studies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Alberta Health Services; University of Alberta; University of Calgary","funders":"","keywords":"Blood pressure; Medicine; Medical prescription; Medical record; Diagnosis code; Antihypertensive drug; Emergency medicine; Prevalence; Internal medicine; Intensive care medicine; Pediatrics; Epidemiology; Pharmacology; Population; Environmental health","score_opus":0.32187560396513953,"score_gpt":0.514501394468662,"score_spread":0.19262579050352252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607131258","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92689514,0.0030328243,0.031923775,0.019892829,0.011257572,0.0010732951,0.0031171378,0.00006384017,0.0027435776],"genre_scores_gemma":[0.9753244,0.0006139817,0.020395126,0.00064541685,0.00028690227,0.000002771148,0.0026823264,0.000009953788,0.000039143713],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99674475,0.00011319071,0.0006417524,0.00045454633,0.0018163546,0.00022942445],"domain_scores_gemma":[0.996001,0.0005231256,0.0005964318,0.0009061033,0.0018610244,0.00011232262],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.012541815,0.00010322601,0.00030462176,0.00039640773,0.00044442594,0.00017815415,0.002575161,0.000071644485,0.00003335784],"category_scores_gemma":[0.026497722,0.00008552819,0.000036759553,0.00016389704,0.00020064526,0.002275328,0.001149574,0.00027418835,0.0000038996823],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007449659,0.00042715628,0.75511175,0.00003096376,0.00038262425,0.000040717565,0.00009507446,0.00011138701,0.0043027764,0.0029041616,0.018228011,0.21762043],"study_design_scores_gemma":[0.0019509973,0.00007407485,0.8829647,0.00030739835,0.00008334142,0.00032671276,0.000037580725,0.09901842,0.0003281799,0.0014330297,0.013325871,0.00014975037],"about_ca_topic_score_codex":0.00063251035,"about_ca_topic_score_gemma":0.000635819,"teacher_disagreement_score":0.21747069,"about_ca_system_score_codex":0.00007452673,"about_ca_system_score_gemma":0.0009052777,"threshold_uncertainty_score":0.9817025},"labels":[],"label_agreement":null},{"id":"W2607220757","doi":"10.23889/ijpds.v1i1.178","title":"Collateral benefits: Unintended consequences of the Roots of Empathy program","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health","funders":"","keywords":"Psychology; Empathy; Clinical psychology; Social psychology","score_opus":0.7139902913886712,"score_gpt":0.710004117309539,"score_spread":0.003986174079132154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607220757","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97032964,0.000008736461,0.00041414463,0.018611874,0.0073541873,0.0010501074,0.0015078174,0.000014311616,0.0007091658],"genre_scores_gemma":[0.9943993,0.000015135033,0.0045491597,0.0006397331,0.00020838906,0.000025317056,0.000025660962,0.0000052230635,0.00013207195],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99693274,0.0001531573,0.0010590963,0.00024841412,0.0012724673,0.00033414527],"domain_scores_gemma":[0.99412906,0.00032062703,0.0025098997,0.0008507752,0.002057959,0.00013165169],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004332135,0.00008148711,0.00016127269,0.00020246688,0.0022683742,0.00013118963,0.005099867,0.00004318653,0.000084316336],"category_scores_gemma":[0.007843684,0.00005532527,0.00004778146,0.00023171764,0.0015737889,0.0021835326,0.0008483587,0.0001982717,0.0000038968933],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001461467,0.000085486136,0.87837815,0.00007242789,0.000039693503,0.0000011703384,0.0026731568,0.00021153051,0.0069808546,0.060578965,0.00425849,0.046573937],"study_design_scores_gemma":[0.00084327365,0.0000745075,0.97846055,0.0002823618,0.00000988433,0.00001676272,0.0007806827,0.002806803,0.0010362343,0.0051624035,0.010445719,0.000080840466],"about_ca_topic_score_codex":0.0012285559,"about_ca_topic_score_gemma":0.00071847055,"teacher_disagreement_score":0.10008238,"about_ca_system_score_codex":0.00016558816,"about_ca_system_score_gemma":0.0015925127,"threshold_uncertainty_score":0.99903053},"labels":[],"label_agreement":null},{"id":"W2607227275","doi":"10.23889/ijpds.v1i1.343","title":"Using Linked Data to Explore the Relationship Between Walking-Friendliness of Neighbourhoods, Physical Activity and Body Mass","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada; McGill University Health Centre; McGill University","funders":"","keywords":"Walkability; Neighbourhood (mathematics); Physical activity; Environmental health; Geography; Built environment; Level design; Gerontology; Medicine; Psychology; Ecology; Computer science; Physical therapy","score_opus":0.47196979582674214,"score_gpt":0.5197015571610791,"score_spread":0.047731761334336986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607227275","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9766652,0.0000062875497,0.018278189,0.0034145506,0.00090845866,0.00020919336,0.00044089922,0.000008627251,0.00006856611],"genre_scores_gemma":[0.9957189,0.0000031862314,0.0029936002,0.00001650973,0.0011246841,0.0000016205374,0.00011018597,0.000005049605,0.000026253916],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99817854,0.000061705214,0.00024641742,0.00036679264,0.0009570468,0.00018948087],"domain_scores_gemma":[0.9976281,0.00040022616,0.0005001604,0.00094499456,0.00039579684,0.00013071726],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0029131703,0.000078529956,0.00012638725,0.000103836115,0.0025536343,0.0008698565,0.005001087,0.000035567762,0.0000072225057],"category_scores_gemma":[0.005031545,0.00005945341,0.000029361136,0.0001627131,0.0005807217,0.006064205,0.00061406597,0.00016667623,7.0056655e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024277122,0.000025884941,0.98945135,0.0000030396652,0.000009691359,5.628852e-7,0.000655104,0.000022461723,0.00047028225,0.0035934257,0.000027736914,0.0057162005],"study_design_scores_gemma":[0.00015689715,0.000008629147,0.9827331,0.00003637396,0.000025137719,7.910061e-7,0.00023639681,0.008491557,0.00003984509,0.0076926243,0.0005033061,0.000075345284],"about_ca_topic_score_codex":0.0024641645,"about_ca_topic_score_gemma":0.00058622,"teacher_disagreement_score":0.01905368,"about_ca_system_score_codex":0.00007281869,"about_ca_system_score_gemma":0.000257674,"threshold_uncertainty_score":0.9987449},"labels":[],"label_agreement":null},{"id":"W2607330690","doi":"10.23889/ijpds.v1i1.340","title":"One for all, all for one - Establishing a corporate linkage methodology for integrated health analytics in Canada","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Linkage (software); False positive paradox; Health care; Analytics; Record linkage; Business; Data science; Data mining; Computer science; Process management; Medicine; Environmental health; Political science","score_opus":0.4665616203419106,"score_gpt":0.45057509304743654,"score_spread":0.015986527294474084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607330690","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13835241,0.000059645467,0.78423065,0.06496742,0.007675999,0.0025037804,0.0021358333,0.000041108022,0.000033135526],"genre_scores_gemma":[0.89967114,0.000020043502,0.09405222,0.0029000044,0.001267984,0.0000912076,0.0019168844,0.00002256105,0.00005797827],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99786025,0.00001838695,0.00079430867,0.00043882782,0.00041353423,0.00047470408],"domain_scores_gemma":[0.9958174,0.00033821748,0.0019690052,0.00045300857,0.0013727216,0.000049621274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006138914,0.0001256994,0.0003244722,0.000546453,0.0007278226,0.0010364637,0.0023973188,0.00007259947,0.000005385195],"category_scores_gemma":[0.008232278,0.00012501124,0.000051591545,0.00017624244,0.00007090158,0.0036554316,0.00030292445,0.00017071926,5.3192724e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085892127,0.00022816185,0.08539761,0.000830417,0.0003019117,0.000008935346,0.00010831009,0.0015259432,0.0012401583,0.41441628,0.023106664,0.47197667],"study_design_scores_gemma":[0.0028279042,0.00010057751,0.045604154,0.00032667318,0.000043181328,0.000014955492,0.00029137172,0.52135354,0.00004817542,0.08364403,0.34539765,0.00034780067],"about_ca_topic_score_codex":0.64881164,"about_ca_topic_score_gemma":0.8675604,"teacher_disagreement_score":0.7613187,"about_ca_system_score_codex":0.00071279466,"about_ca_system_score_gemma":0.0013461111,"threshold_uncertainty_score":0.9994643},"labels":[],"label_agreement":null},{"id":"W2607372085","doi":"10.23889/ijpds.v1i1.71","title":"Developing and Validating Electronic Medical Record Based Case Definitions for Liver Diseases and Comorbidities","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Comorbidity; Electronic medical record; Cirrhosis; Diabetes mellitus; Gold standard (test); Medical record; Liver disease; Internal medicine; Electronic health record; Kappa; Hepatitis C; Disease; Emergency medicine; Health care","score_opus":0.2594944024115622,"score_gpt":0.4585644835940625,"score_spread":0.1990700811825003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607372085","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8691599,0.00031059995,0.11414044,0.013062652,0.0014181093,0.0006676758,0.0009510682,0.00004274067,0.00024683203],"genre_scores_gemma":[0.9863246,0.00027038372,0.012325593,0.00031291528,0.00031573127,0.000017068469,0.00039868557,0.0000072534003,0.000027732189],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988516,0.000010090476,0.00022220508,0.0002493598,0.0004825472,0.00018421952],"domain_scores_gemma":[0.9989397,0.00017994574,0.00021084379,0.00024451694,0.00027277536,0.00015221084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006735645,0.000077147735,0.000099239194,0.00015593028,0.0011370294,0.00075269537,0.00046060816,0.000020554202,0.00004506489],"category_scores_gemma":[0.0028511148,0.000069445014,0.000025958503,0.000033874072,0.00027270574,0.0015195643,0.0002695592,0.000077042045,4.818484e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061379245,0.00023169293,0.2054274,0.00048469234,0.00031895415,0.0010363173,0.00013957247,0.00005571628,0.00009354531,0.54991466,0.0047181365,0.23696555],"study_design_scores_gemma":[0.006610048,0.0002914902,0.41209102,0.0011063683,0.0004334231,0.005422962,0.00066275784,0.50443506,0.000048231486,0.04816409,0.020265367,0.00046916908],"about_ca_topic_score_codex":0.00015438955,"about_ca_topic_score_gemma":0.00019045187,"teacher_disagreement_score":0.5043794,"about_ca_system_score_codex":0.0001433309,"about_ca_system_score_gemma":0.00060779176,"threshold_uncertainty_score":0.87452257},"labels":[],"label_agreement":null},{"id":"W2607375727","doi":"10.23889/ijpds.v1i1.266","title":"Linking Hospital and Tax data to support research on the economic impacts of hospitalization","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Sunnybrook Hospital; Statistics Canada","funders":"","keywords":"Linkage (software); Record linkage; Income tax; Data source; Actuarial science; Health insurance; Database; Business; Medicine; Health care; Economics; Public economics; Computer science; Environmental health; Economic growth; Genetics","score_opus":0.40017066413592006,"score_gpt":0.49272687100635554,"score_spread":0.09255620687043548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607375727","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9290243,0.00004323934,0.0052914512,0.05578174,0.0037753198,0.00057513727,0.0040364866,0.0000066904518,0.001465674],"genre_scores_gemma":[0.9981995,0.00012659581,0.00080860895,0.00025428046,0.00034857017,0.000004213888,0.00018574685,0.000005999931,0.00006646752],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9988218,0.000012707166,0.00042849977,0.00035543396,0.00018621779,0.00019534683],"domain_scores_gemma":[0.9980577,0.00008727288,0.0005170416,0.0010829994,0.00015810152,0.00009685844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006202386,0.00005559498,0.00009782441,0.00035735025,0.00077852554,0.0006806983,0.003630792,0.000022867953,0.000028353894],"category_scores_gemma":[0.0024905354,0.00004879278,0.000015126328,0.00006787054,0.00014050696,0.0023033775,0.0013587307,0.00010385148,0.000030705945],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021639256,0.000028141263,0.107829586,0.000009612398,0.00002298052,0.0000011732739,0.00025060668,0.00017852828,0.000011087269,0.87531507,0.0070162634,0.009315299],"study_design_scores_gemma":[0.00045129293,0.00036834818,0.7502523,0.000112582115,0.0000038913636,0.000008465132,0.0001465686,0.05209224,0.000051880495,0.06090327,0.13541557,0.00019358468],"about_ca_topic_score_codex":0.0026674136,"about_ca_topic_score_gemma":0.00041674453,"teacher_disagreement_score":0.8144118,"about_ca_system_score_codex":0.00018491298,"about_ca_system_score_gemma":0.00010401467,"threshold_uncertainty_score":0.6746975},"labels":[],"label_agreement":null},{"id":"W2607388123","doi":"10.23889/ijpds.v1i1.47","title":"General Public Views on Uses and Users of Administrative Health Data","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Public health; Business; Public relations; Internet privacy; Information privacy; Agency (philosophy); Medicine; Political science; Nursing; Computer science; Sociology","score_opus":0.7371393720034938,"score_gpt":0.6781846523944396,"score_spread":0.058954719609054185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607388123","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75902236,0.00012607001,0.0039492026,0.21122324,0.01686618,0.0011793121,0.005633017,0.000027887216,0.001972713],"genre_scores_gemma":[0.98726124,0.00037141456,0.0057931324,0.0032652786,0.0016083898,0.0000131569495,0.0012240498,0.000009975669,0.00045339428],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99771166,0.00013915519,0.0007384765,0.00036673725,0.00067073066,0.00037325703],"domain_scores_gemma":[0.9959426,0.00024926104,0.001563828,0.001255528,0.00066997594,0.00031879047],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005253788,0.000090085014,0.00017491564,0.00024499974,0.0030407917,0.00030435575,0.0034828945,0.000045519286,0.000054684908],"category_scores_gemma":[0.0055135884,0.00007343417,0.00001686559,0.000090098045,0.0002483506,0.0042701056,0.0009063933,0.00025051384,0.000006006463],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017298499,0.00026802238,0.41761115,0.00014528644,0.00007070164,0.0000013884919,0.0032411343,0.000020179861,0.00014769794,0.20667018,0.24438311,0.12726815],"study_design_scores_gemma":[0.0005795991,0.00012350341,0.6513909,0.00017852189,0.0000046931978,0.000012415683,0.00084660796,0.009025652,0.000003947797,0.0017101684,0.33602545,0.000098548044],"about_ca_topic_score_codex":0.002901166,"about_ca_topic_score_gemma":0.001423169,"teacher_disagreement_score":0.23377976,"about_ca_system_score_codex":0.00023176563,"about_ca_system_score_gemma":0.0024374255,"threshold_uncertainty_score":0.9982571},"labels":[],"label_agreement":null},{"id":"W2607417062","doi":"10.23889/ijpds.v1i1.39","title":"Barriers to high quality coding of hospital chart information to administrative data: A qualitative study","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Coding (social sciences); Thematic analysis; Medical classification; Data quality; Computer science; Qualitative research; Psychology; Medical education; Medicine; Nursing; Business; Service (business); Marketing; Sociology","score_opus":0.6170284871732151,"score_gpt":0.6686811027960435,"score_spread":0.05165261562282841,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607417062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91158986,0.0000015403145,0.05576425,0.0165754,0.009263685,0.0020165825,0.004189952,0.000026884609,0.00057186227],"genre_scores_gemma":[0.9917788,0.000004331871,0.005735876,0.0011174233,0.0004608326,0.0000456549,0.0007834427,0.0000049401933,0.00006870596],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.9960123,0.00023749663,0.0014873781,0.00030312897,0.0016269727,0.00033273184],"domain_scores_gemma":[0.9938476,0.0004707498,0.0017885739,0.0011504579,0.002095599,0.0006470264],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.014190638,0.00011517074,0.0002395191,0.00037872847,0.0030965821,0.00030076236,0.004023183,0.000056412253,0.000118664044],"category_scores_gemma":[0.042939257,0.00009938502,0.00002286145,0.00018459321,0.00011618061,0.009353683,0.0013416266,0.00032590874,0.00006313502],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002086518,0.00036941117,0.25273627,0.00033209007,0.00022774853,0.0000042567826,0.54105616,0.0002697042,0.00019465991,0.10587357,0.056963343,0.039886285],"study_design_scores_gemma":[0.002895916,0.0012767144,0.7576478,0.0006788151,0.000033349414,0.0000026671823,0.20291652,0.007806912,0.000036996036,0.0019694022,0.02432728,0.00040763622],"about_ca_topic_score_codex":0.0016507122,"about_ca_topic_score_gemma":0.00038646258,"teacher_disagreement_score":0.50491154,"about_ca_system_score_codex":0.0003103332,"about_ca_system_score_gemma":0.0012378906,"threshold_uncertainty_score":0.99820125},"labels":[],"label_agreement":null},{"id":"W2607422284","doi":"10.23889/ijpds.v1i1.87","title":"Discharge Communication and Patient Involvement are Associated with Unplanned Hospital Readmissions: Results from a Validated Hospital Experience Survey","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Patient Satisfaction in Healthcare","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Confidence interval; Logistic regression; Health care; Odds ratio; Hospital discharge; Odds; Emergency medicine; Telephone survey; Telephone interview; Cohort; Acute care; Medical emergency; Family medicine; Intensive care medicine; Internal medicine","score_opus":0.21017788553659217,"score_gpt":0.48170562551057433,"score_spread":0.27152773997398216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607422284","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9800136,0.000037820864,0.0005553844,0.0050166147,0.0033824649,0.0009073819,0.009998221,0.000042150736,0.000046364796],"genre_scores_gemma":[0.99064386,0.000099261815,0.0020046271,0.00021386301,0.00011458005,0.000074153104,0.0067709596,0.000017450555,0.000061272585],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9963745,0.0003880905,0.0009796419,0.0006220972,0.0012472366,0.0003884235],"domain_scores_gemma":[0.9924789,0.0008860624,0.0029824467,0.0013324437,0.0019984595,0.0003216964],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.0020732256,0.00018202778,0.00021895512,0.00019027643,0.0051466995,0.00042422154,0.0021851931,0.000106021434,0.000040761777],"category_scores_gemma":[0.016674658,0.00014699296,0.000024382494,0.00014863179,0.00031263113,0.004033392,0.001018322,0.00041180555,0.0000063554935],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025499598,0.00007163765,0.9926431,0.0000033679728,0.00003423798,0.0000026671003,0.0035345596,0.000016045791,0.000034807243,0.00015336677,0.0021447672,0.0011064463],"study_design_scores_gemma":[0.0016359461,0.00016569579,0.98985964,0.0008316513,0.000010634383,0.0000015603193,0.0027684239,0.0030954916,0.000027375983,0.00043108696,0.00097077293,0.0002016992],"about_ca_topic_score_codex":0.0080308495,"about_ca_topic_score_gemma":0.0042228717,"teacher_disagreement_score":0.014601432,"about_ca_system_score_codex":0.0005248584,"about_ca_system_score_gemma":0.00035809365,"threshold_uncertainty_score":0.99857473},"labels":[],"label_agreement":null},{"id":"W2607431720","doi":"10.23889/ijpds.v1i1.232","title":"Chronic Disease Case Definitions for Electronic Medical Records: A Canadian Validation Study","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"","keywords":"Medicine; Medical record; COPD; Medical prescription; Cohort; Depression (economics); Medical diagnosis; Diagnosis code; Population; Prescription drug; Family medicine; Cohort study; Emergency medicine; Internal medicine; Environmental health","score_opus":0.19416953744420765,"score_gpt":0.47172771008298214,"score_spread":0.27755817263877447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607431720","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92921376,0.00019858035,0.019507106,0.035342604,0.0071247923,0.004042355,0.0028019499,0.000087214576,0.0016816177],"genre_scores_gemma":[0.99622595,0.000059993105,0.0004807645,0.00018007313,0.0012837863,0.00008471341,0.0014758075,0.000014641979,0.00019423896],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977051,0.00001872956,0.00038168998,0.00043765272,0.0010504883,0.0004063234],"domain_scores_gemma":[0.9975133,0.00006519584,0.00029695983,0.0008420618,0.00061673747,0.00066577893],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0016519862,0.00012025868,0.00012956742,0.00043255978,0.0017875811,0.0010096619,0.0015892102,0.00003057724,0.00029295476],"category_scores_gemma":[0.0041081384,0.000112970716,0.000074366195,0.00009942851,0.00016593114,0.0023654639,0.0002383295,0.00015491452,0.000010389528],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018483157,0.002327326,0.41961107,0.00030069647,0.0015450278,0.009919397,0.0004024147,0.0012609926,0.00008872789,0.26410332,0.03905911,0.2595336],"study_design_scores_gemma":[0.013937369,0.0012379775,0.6140401,0.00056548126,0.0010839661,0.0050676013,0.0009063165,0.25252187,0.000018149962,0.033204053,0.07664824,0.0007688889],"about_ca_topic_score_codex":0.011010982,"about_ca_topic_score_gemma":0.07348384,"teacher_disagreement_score":0.2587647,"about_ca_system_score_codex":0.0013297478,"about_ca_system_score_gemma":0.005110087,"threshold_uncertainty_score":0.99951196},"labels":[],"label_agreement":null},{"id":"W2607479514","doi":"10.23889/ijpds.v1i1.75","title":"Understanding variations in the trajectories of academic achievement and mental health service utilization of foreign-born adolescents in British Columbia, Canada: A population-based cohort study","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mental health; Academic achievement; Cohort; Psychology; Population; Multinomial logistic regression; Service (business); Odds ratio; Demography; Medicine; Developmental psychology; Psychiatry; Sociology; Economics","score_opus":0.14561137073536104,"score_gpt":0.41812055723706654,"score_spread":0.2725091865017055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607479514","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9936682,0.000031935993,0.0027114754,0.0011771874,0.00077319436,0.0009787729,0.00064196374,0.0000024878275,0.000014773619],"genre_scores_gemma":[0.9990386,0.000016005937,0.00016686521,0.00020257798,0.00004604048,0.000018886532,0.00050100154,0.0000050274402,0.0000050228186],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99791116,0.000118269396,0.0007398888,0.00025609467,0.00079519686,0.0001794059],"domain_scores_gemma":[0.99851835,0.00007791732,0.0008286969,0.0002985529,0.00021529204,0.000061203136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025496967,0.00006165407,0.00015091081,0.0001710676,0.00062492816,0.00020127522,0.00094811036,0.000032533208,0.00001614347],"category_scores_gemma":[0.0003081545,0.00007381024,0.000012993762,0.00024135962,0.000054200347,0.0007857916,0.00006111957,0.00014698965,5.6194263e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000341686,0.0001473857,0.9961795,0.000018271401,0.00001025417,8.096071e-7,0.0011140734,0.00011785279,0.000002219192,0.0014805464,0.00012387162,0.0007710507],"study_design_scores_gemma":[0.0012159457,0.000054750144,0.98767066,0.00014446006,0.0000061785586,0.00000904162,0.002892689,0.0071392045,3.31984e-7,0.000795484,0.000016720716,0.000054515047],"about_ca_topic_score_codex":0.8980487,"about_ca_topic_score_gemma":0.9920823,"teacher_disagreement_score":0.094033554,"about_ca_system_score_codex":0.0005172466,"about_ca_system_score_gemma":0.0006315196,"threshold_uncertainty_score":0.48065054},"labels":[],"label_agreement":null},{"id":"W2610567509","doi":"10.23889/ijpds.v1i1.182","title":"Constructing episodes of inpatient care: How to define hospital transfer in hospital administrative health data?","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Medicine; Transfer (computing); Health care; Emergency medicine; Medical emergency; Pediatrics","score_opus":0.194357924024838,"score_gpt":0.4191685866196027,"score_spread":0.2248106625947647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610567509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79212916,0.00023503037,0.06073599,0.12382813,0.006793349,0.0010478989,0.014413976,0.000012768578,0.00080368796],"genre_scores_gemma":[0.9894393,0.00006444377,0.009687452,0.00017744495,0.00016612222,0.0000069887824,0.0004367453,0.0000063990697,0.000015111091],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99843735,0.000011873322,0.00066810986,0.000446268,0.00019136457,0.0002450664],"domain_scores_gemma":[0.9982917,0.000037619022,0.0006093728,0.00072867045,0.00019734749,0.00013531675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015572747,0.00008908541,0.0002143133,0.00036256987,0.00034388065,0.00041012722,0.0026178788,0.000025068746,0.000009529831],"category_scores_gemma":[0.0017470869,0.00009735477,0.000029506817,0.000113684975,0.00013111874,0.0026728588,0.0005234801,0.0001092345,0.0000034994669],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039947747,0.000167609,0.33047783,0.000049894723,0.000036791716,0.000004685656,0.002614079,0.00008259022,0.000003793603,0.60277534,0.00092953624,0.06281788],"study_design_scores_gemma":[0.0025995267,0.00144885,0.9020851,0.00040509275,0.000008198389,0.000022199129,0.0046140687,0.014637202,0.0001358996,0.01764525,0.05573173,0.00066687004],"about_ca_topic_score_codex":0.004391693,"about_ca_topic_score_gemma":0.002790963,"teacher_disagreement_score":0.5851301,"about_ca_system_score_codex":0.00032076417,"about_ca_system_score_gemma":0.00018107991,"threshold_uncertainty_score":0.66389555},"labels":[],"label_agreement":null},{"id":"W2611896270","doi":"10.23889/ijpds.v1i1.331","title":"Increasing research capacity with ICES Data &amp; Analytic Services (DAS)","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Deliverable; Business; Health care; Reputation; Population; Data science; Computer science; Medicine; Political science; Environmental health; Engineering","score_opus":0.5874081624918781,"score_gpt":0.6525756916735266,"score_spread":0.06516752918164848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2611896270","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9627288,0.00005567575,0.0025748129,0.02227711,0.0047107823,0.000643436,0.0019531958,0.000044741653,0.0050114235],"genre_scores_gemma":[0.9747535,0.00013963565,0.019596757,0.0017425087,0.0016644171,0.000010227483,0.0015080828,0.000016173739,0.000568713],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99595517,0.00026684595,0.00059605937,0.00061032857,0.0019769564,0.00059461157],"domain_scores_gemma":[0.99342954,0.00076963776,0.00086618704,0.0025447214,0.002122174,0.00026776193],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.01439178,0.0001179325,0.000196376,0.0004670289,0.008320022,0.00087302114,0.0101346765,0.000071524686,0.00013028279],"category_scores_gemma":[0.003715018,0.000088111665,0.000021979946,0.00021061886,0.0003676732,0.009360131,0.0032318472,0.0007344893,0.00007044187],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030529307,0.00004176918,0.97623813,0.000098190154,0.000049389324,0.000007843923,0.00043457642,0.000017500975,0.00023062702,0.003559022,0.010697754,0.008319886],"study_design_scores_gemma":[0.0008290318,0.00003773259,0.7788778,0.00035965085,0.00002511509,0.00007513414,0.00041192502,0.009024957,0.0000037567984,0.0035255365,0.20666286,0.00016652924],"about_ca_topic_score_codex":0.014455976,"about_ca_topic_score_gemma":0.022493158,"teacher_disagreement_score":0.19736038,"about_ca_system_score_codex":0.0006186723,"about_ca_system_score_gemma":0.0017978125,"threshold_uncertainty_score":0.9953438},"labels":[],"label_agreement":null},{"id":"W2612991029","doi":"10.23889/ijpds.v1i1.88","title":"Institute for Clinical Evaluative Sciences (ICES) Exploratory Data &amp; Analytic Services Private Sector Pilot Project","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Private sector; Public sector; Transparency (behavior); Work (physics); Government (linguistics); Business; Public relations; Engineering; Computer science; Political science; Computer security","score_opus":0.8638775734662381,"score_gpt":0.692514129968013,"score_spread":0.17136344349822508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612991029","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90783316,0.00007081978,0.05968104,0.014362682,0.012052523,0.0023093962,0.0034762553,0.00005447986,0.0001596479],"genre_scores_gemma":[0.86476314,0.00022382475,0.124859564,0.001524289,0.0030262205,0.00003283598,0.0054401676,0.000020245358,0.00010972846],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952774,0.00009678695,0.0015455721,0.00097156316,0.0017951584,0.000313531],"domain_scores_gemma":[0.9930242,0.0008627211,0.0021300577,0.0018102304,0.0019740171,0.00019881173],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.016534867,0.00016726226,0.00029152,0.00036202505,0.0018180273,0.0014717164,0.005912755,0.000049360573,0.000036024154],"category_scores_gemma":[0.025065344,0.00013523264,0.000080868005,0.00023065029,0.0008270498,0.015013791,0.00162949,0.00025991563,0.000014646035],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004292597,0.0012781924,0.87038195,0.00018215088,0.0007799761,0.000021856267,0.00035660723,0.0005508391,0.0024909982,0.0044930866,0.026534034,0.088637695],"study_design_scores_gemma":[0.0071284366,0.0011686537,0.40981108,0.00044598992,0.000599088,0.00020505425,0.00039645936,0.41969717,0.000059872225,0.0037415884,0.15633012,0.00041646772],"about_ca_topic_score_codex":0.0006035413,"about_ca_topic_score_gemma":0.0017472173,"teacher_disagreement_score":0.46057087,"about_ca_system_score_codex":0.00017770045,"about_ca_system_score_gemma":0.0017055135,"threshold_uncertainty_score":0.9995648},"labels":[],"label_agreement":null},{"id":"W2763858017","doi":"10.23889/ijpds.v2i1.407","title":"Family Matters: High School Graduation and Sibling Influence","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cognitive Abilities and Testing","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"","keywords":"Sibling; Birth order; Educational attainment; Odds; Graduation (instrument); Demography; Logistic regression; Confounding; Psychology; Odds ratio; Developmental psychology; Population; Gerontology; Medicine; Sociology","score_opus":0.14601347923580638,"score_gpt":0.4528837391657612,"score_spread":0.3068702599299548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763858017","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98632896,0.000031544718,0.0064279255,0.0037211734,0.0027961757,0.00013382907,0.00015119412,0.000016665657,0.00039252467],"genre_scores_gemma":[0.99470925,0.000013488373,0.0038327575,0.0007440562,0.0004603342,0.000006572392,0.000074393174,0.0000067826663,0.00015238886],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99871105,0.000020161617,0.00028362204,0.00034165918,0.00045933566,0.00018415047],"domain_scores_gemma":[0.9982487,0.00015803597,0.00039854686,0.0004460839,0.00064187957,0.00010674551],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012240827,0.00007777008,0.00007549502,0.00021584876,0.0010905415,0.0014195589,0.0014516413,0.000024839726,0.00007518233],"category_scores_gemma":[0.003235432,0.00007319233,0.00001943661,0.00006451033,0.00022930195,0.004017935,0.00040540847,0.00012536791,0.000019498508],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000102429665,0.000056451554,0.8108772,0.000007710569,0.00005288438,0.000015964268,0.00028536736,0.00015267264,0.0031335899,0.031706374,0.0022233552,0.151386],"study_design_scores_gemma":[0.0004709255,0.000027779179,0.9825805,0.00005969121,0.0000091342845,0.00008129745,0.00018580753,0.003253021,0.000015742577,0.011654506,0.0015679329,0.000093653296],"about_ca_topic_score_codex":0.0014167364,"about_ca_topic_score_gemma":0.000042668795,"teacher_disagreement_score":0.1717033,"about_ca_system_score_codex":0.00006677728,"about_ca_system_score_gemma":0.00005973089,"threshold_uncertainty_score":0.99961704},"labels":[],"label_agreement":null},{"id":"W2786827563","doi":"10.23889/ijpds.v3i1.419","title":"Using the RECORD guidelines to improve transparent reporting of studies based on routinely collected data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of Ottawa","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Wellcome Trust","keywords":"Observational study; Data science; Key (lock); Health care; Quality (philosophy); Data quality; Computer science; Data mining; Medicine; Operations management; Engineering; Computer security","score_opus":0.970685801615776,"score_gpt":0.7130115155502669,"score_spread":0.25767428606550913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2786827563","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22218531,0.00009400894,0.7592977,0.009498382,0.007058669,0.00090666,0.00078299124,0.000005492379,0.00017076763],"genre_scores_gemma":[0.8600254,0.000005955799,0.13822222,0.0006975084,0.0006647255,0.000004775983,0.000052893432,0.000006443953,0.00032005963],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9795968,0.00070705067,0.011887689,0.000954504,0.0066604842,0.00019350175],"domain_scores_gemma":[0.95198816,0.0024946514,0.02076228,0.0059693996,0.018633395,0.00015210857],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.15303029,0.00015221664,0.00094299414,0.00059382914,0.0006143097,0.0010653029,0.009847829,0.000022165766,0.00023435723],"category_scores_gemma":[0.3457011,0.00006783657,0.00024083654,0.0016298578,0.00016956021,0.0012839078,0.0006973778,0.00008902644,0.000016999838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055221585,0.00027599488,0.30570003,0.000060906572,0.0010384276,0.0000141598175,0.001519106,0.058902156,0.011887283,0.0030201664,0.30395523,0.31307432],"study_design_scores_gemma":[0.00016566028,0.000074706775,0.018944534,0.00015418851,0.00008123964,0.00001995991,0.00036353938,0.9624191,0.00016026286,0.0013940921,0.01612833,0.00009439516],"about_ca_topic_score_codex":0.00010538408,"about_ca_topic_score_gemma":0.00028099152,"teacher_disagreement_score":0.90351695,"about_ca_system_score_codex":0.00009867649,"about_ca_system_score_gemma":0.00032360986,"threshold_uncertainty_score":0.9999717},"labels":[],"label_agreement":null},{"id":"W2788138713","doi":"10.23889/ijpds.v3i1.415","title":"Position Statement on Population Data Science:","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Statistics Canada; University of Calgary; Manitoba Health; University of British Columbia","funders":"Economic and Social Research Council; Medical Research Council","keywords":"Data science; Population; Field (mathematics); Computer science; Discipline; Analytics; Public engagement; Informatics; Big data; Engineering ethics; Knowledge management; Sociology; Public relations; Political science; Data mining; Social science; Engineering","score_opus":0.09722525678110634,"score_gpt":0.4376056193179299,"score_spread":0.3403803625368236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2788138713","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95500535,0.000006161021,0.033216506,0.0037566745,0.004302535,0.00068576174,0.00081308687,0.00004989795,0.0021640277],"genre_scores_gemma":[0.98506993,0.00002941303,0.011744293,0.0011021149,0.0006721485,0.0000069654825,0.0012697639,0.000015739162,0.00008961641],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9945631,0.00006524516,0.0006362876,0.0012686028,0.0029332384,0.0005335112],"domain_scores_gemma":[0.9975917,0.00008462517,0.0005071551,0.0013319368,0.0001855457,0.00029909008],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0065596686,0.00017138729,0.00011876012,0.000397138,0.0017098457,0.00064511533,0.0046267645,0.00004052124,0.0007364811],"category_scores_gemma":[0.0013801093,0.00015911723,0.000025355901,0.0006745627,0.0009324473,0.011055335,0.0019933512,0.00020748313,0.0003550637],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005048343,0.0008124409,0.4597442,0.000014118553,0.000063480365,0.00003070469,0.0008559135,0.0064534554,0.060271747,0.010455515,0.017921822,0.44287178],"study_design_scores_gemma":[0.00058103056,0.00019957437,0.8395335,0.000062463856,0.000016047135,0.000057985337,0.0000814346,0.13433684,0.0007109914,0.0028174738,0.021329293,0.00027334254],"about_ca_topic_score_codex":0.0008531043,"about_ca_topic_score_gemma":0.000265125,"teacher_disagreement_score":0.44259843,"about_ca_system_score_codex":0.0017630499,"about_ca_system_score_gemma":0.00015620665,"threshold_uncertainty_score":0.9995898},"labels":[],"label_agreement":null},{"id":"W2804792234","doi":"10.23889/ijpds.v3i1.450","title":"Unlocking First Nations health information through data linkage","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Laurentian University; Institute for Work & Health; Sunnybrook Health Science Centre; Institute for Clinical Evaluative Sciences","funders":"Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences","keywords":"Indigenous; Linkage (software); Sovereignty; Context (archaeology); Linked data; Population; Record linkage; Geography; Metis; Economic growth; Database; Political science; Medicine; Environmental health; Biology; Law; Genetics; Ecology; World Wide Web; Computer science; Economics; Politics","score_opus":0.47246174585891115,"score_gpt":0.5651324642231068,"score_spread":0.09267071836419566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804792234","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024377913,0.000037911774,0.946075,0.032021414,0.010508704,0.00045371012,0.005367042,0.00005769749,0.003040721],"genre_scores_gemma":[0.9155758,0.00018388356,0.06947912,0.0046719294,0.0018238648,0.000007279039,0.0078686895,0.000009990669,0.00037944363],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99393785,0.00008994499,0.0013254663,0.0006144062,0.0037026221,0.00032969675],"domain_scores_gemma":[0.99366176,0.0007339417,0.0011836615,0.0021994838,0.0020582657,0.00016286003],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0150215225,0.00012217536,0.00016151438,0.00090945355,0.0025226143,0.0036161377,0.012534098,0.000034943125,0.00022361148],"category_scores_gemma":[0.022064902,0.000100208425,0.0000395053,0.0013584323,0.00031683038,0.03518074,0.0034437547,0.00014513293,0.00028703728],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080475234,0.00014537982,0.004913412,0.00001760362,0.0000661957,0.0000023008588,0.0021338537,0.0010273585,0.0000133874455,0.29390606,0.39314875,0.30454522],"study_design_scores_gemma":[0.00035729885,0.000053033127,0.0108972,0.000055100936,0.0000060181865,0.000030320267,0.0005465501,0.08033777,0.000010471292,0.021300597,0.8862786,0.0001270181],"about_ca_topic_score_codex":0.0005746934,"about_ca_topic_score_gemma":0.0030173354,"teacher_disagreement_score":0.91313803,"about_ca_system_score_codex":0.00022939575,"about_ca_system_score_gemma":0.0004263196,"threshold_uncertainty_score":0.99877596},"labels":[],"label_agreement":null},{"id":"W2808764968","doi":"10.23889/ijpds.v3i2.523","title":"Measuring Active Living Environments: An international comparison between Canada and Wales","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"","keywords":"Walkability; Neighbourhood (mathematics); Built environment; Geography; Context (archaeology); Geographic information system; Work (physics); Environmental planning; Environmental health; Environmental resource management; Transport engineering; Cartography; Environmental science; Civil engineering; Engineering; Medicine","score_opus":0.1417070515434685,"score_gpt":0.4077715654693917,"score_spread":0.26606451392592323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808764968","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99186003,0.000010520617,0.0042715673,0.0006049499,0.002427624,0.00010360737,0.00026839992,0.000011691861,0.00044158485],"genre_scores_gemma":[0.99652076,0.000014960939,0.0015359317,0.00006750307,0.0016103745,0.0000016661032,0.00015445477,0.0000049580294,0.000089415924],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977912,0.000046666868,0.00031836575,0.00034696082,0.001280603,0.00021624171],"domain_scores_gemma":[0.99895096,0.000118511845,0.00025128725,0.00019286685,0.00029385986,0.00019251383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015103864,0.000078686695,0.000094424075,0.00012571324,0.0010944066,0.00050224666,0.0019157749,0.000030340603,0.000103646176],"category_scores_gemma":[0.000735511,0.00007670642,0.000016881728,0.00011613877,0.0004500249,0.00549654,0.00018080085,0.00011235329,0.0000013940609],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014669373,0.000023903945,0.9639896,6.577147e-7,0.000019451332,7.3366886e-7,0.0009028524,0.000010503477,0.00011748313,0.0005016413,0.0000777373,0.034340773],"study_design_scores_gemma":[0.00011803868,0.000017311302,0.97896546,0.000026855621,0.0000101394835,0.0000013793579,0.00073583977,0.0016987063,0.000112288064,0.000573954,0.017638803,0.00010120666],"about_ca_topic_score_codex":0.23147179,"about_ca_topic_score_gemma":0.62507457,"teacher_disagreement_score":0.3936028,"about_ca_system_score_codex":0.00046882255,"about_ca_system_score_gemma":0.00042578368,"threshold_uncertainty_score":0.84174013},"labels":[],"label_agreement":null},{"id":"W2809036931","doi":"10.23889/ijpds.v3i2.491","title":"Using administrative data from a national shared services database to target the delivery of homeless services in the Dublin Region","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University","funders":"","keywords":"Outreach; Typology; Service (business); Cluster (spacecraft); Population; Geography; Business; Database; Medicine; Computer science; Political science; Environmental health; Marketing","score_opus":0.4421774678221388,"score_gpt":0.5641765783400537,"score_spread":0.12199911051791495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809036931","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98339266,0.00006907298,0.003987417,0.0020087194,0.0016697624,0.0005106204,0.008207804,0.000008487845,0.00014543769],"genre_scores_gemma":[0.9893853,0.00002453729,0.0049370197,0.0006565291,0.001358129,0.000013516883,0.0036067215,0.000007891703,0.000010322424],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970883,0.00027415686,0.00065410533,0.00039725794,0.0013437222,0.00024241602],"domain_scores_gemma":[0.9963051,0.0005983184,0.0006229508,0.00069347373,0.0017066108,0.00007352263],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0034770886,0.000107531094,0.0001884916,0.0002306173,0.0011401275,0.0002467788,0.005817163,0.000053511034,0.00009194859],"category_scores_gemma":[0.0004670155,0.000068183734,0.000022808656,0.0005632727,0.000161721,0.0036307822,0.0011859777,0.00024124855,0.000011535911],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021433346,0.000800773,0.7334753,0.00031218998,0.00033206795,0.00006379178,0.16818663,0.0010836831,0.0053169406,0.07855228,0.003008373,0.006724623],"study_design_scores_gemma":[0.0013931341,0.00009165233,0.5075339,0.0013642228,0.000044485496,0.000012212704,0.13362218,0.3283267,0.000095409145,0.013455804,0.013734058,0.00032623488],"about_ca_topic_score_codex":0.00883615,"about_ca_topic_score_gemma":0.034284584,"teacher_disagreement_score":0.32724303,"about_ca_system_score_codex":0.00014416238,"about_ca_system_score_gemma":0.0005954279,"threshold_uncertainty_score":0.99956185},"labels":[],"label_agreement":null},{"id":"W2809423523","doi":"10.23889/ijpds.v3i2.552","title":"A Comparison of Mental Health Performance Indicators in Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Women's College Hospital; Institut universitaire en santé mentale de Montréal; University of Calgary; Simon Fraser University","funders":"","keywords":"Mental health; Medicine; Addiction; Demography; Family medicine; Psychiatry","score_opus":0.6546300738231517,"score_gpt":0.7237840988526539,"score_spread":0.06915402502950219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809423523","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98424083,0.000008077365,0.0009186928,0.009067463,0.004460473,0.00045521997,0.0006035743,0.0000060767775,0.00023962176],"genre_scores_gemma":[0.99356717,0.000018152634,0.002868059,0.0031019745,0.00028537866,0.000009914355,0.000100859565,0.0000052281325,0.00004324947],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99641454,0.0001451061,0.0013405635,0.00026032267,0.0013628411,0.0004766221],"domain_scores_gemma":[0.9975033,0.0002762704,0.0011802083,0.00028428144,0.0005301405,0.00022584244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004626689,0.000073305426,0.00017848985,0.0007967341,0.0010038007,0.000024644316,0.001796517,0.000020884312,0.00018271447],"category_scores_gemma":[0.0013742164,0.000067037035,0.000011644501,0.0010145268,0.00017979144,0.0014399131,0.00031736284,0.0002301897,0.000009508925],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032516837,0.0000125142915,0.9719217,0.000014103102,0.0000026801006,1.1281923e-7,0.002368502,0.000022605154,0.00006328475,0.0006015649,0.010385811,0.01457464],"study_design_scores_gemma":[0.00074435043,0.00008886751,0.9105498,0.00015156019,9.495315e-7,0.000004971564,0.002145337,0.024559734,0.00009444105,0.00006349643,0.061519314,0.0000771791],"about_ca_topic_score_codex":0.3686927,"about_ca_topic_score_gemma":0.7144072,"teacher_disagreement_score":0.34571448,"about_ca_system_score_codex":0.002259067,"about_ca_system_score_gemma":0.011257906,"threshold_uncertainty_score":0.99434733},"labels":[],"label_agreement":null},{"id":"W2809441073","doi":"10.23889/ijpds.v3i2.550","title":"Building a Pan-Canadian Real World Health Data Network","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Vector Institute; University of Manitoba; University of New Brunswick; Canadian Institute for Health Information; University of British Columbia","funders":"","keywords":"Benchmarking; Harmonization; Data access; Indigenous; Business; Computer science; Data science; Public relations; Political science; Database; Marketing","score_opus":0.2647105010337236,"score_gpt":0.56796727186318,"score_spread":0.30325677082945635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809441073","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06952385,0.0010718118,0.1479151,0.497891,0.20724289,0.0061389604,0.018676812,0.00057096675,0.050968613],"genre_scores_gemma":[0.71035606,0.0006228708,0.16783936,0.08316878,0.029023126,0.000031070016,0.0059007737,0.000063395084,0.002994532],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964556,0.00015665319,0.00094063865,0.0005783448,0.0009145427,0.00095419324],"domain_scores_gemma":[0.99626726,0.00035848445,0.000676262,0.0011849203,0.000912638,0.0006004307],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.007399408,0.00012833595,0.00021519777,0.000618743,0.004013823,0.0001939671,0.005031791,0.00005738743,0.00037531037],"category_scores_gemma":[0.0011874812,0.00011524065,0.000029803121,0.00066185876,0.00016238957,0.0033169405,0.0013217238,0.00046491643,0.000101881116],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006945535,0.000015417481,0.18789074,0.000018054909,0.00002759756,0.0000047188764,0.00019939727,0.000018000816,0.000012973698,0.046106745,0.68416697,0.0814699],"study_design_scores_gemma":[0.00037405037,0.00004099688,0.24234605,0.00011815279,0.0000067259984,0.00001350986,0.000057183956,0.0067344466,4.4500783e-7,0.0056619253,0.7445278,0.000118717806],"about_ca_topic_score_codex":0.11359907,"about_ca_topic_score_gemma":0.5177544,"teacher_disagreement_score":0.64083225,"about_ca_system_score_codex":0.0020217963,"about_ca_system_score_gemma":0.00933229,"threshold_uncertainty_score":0.9972828},"labels":[],"label_agreement":null},{"id":"W2809519624","doi":"10.23889/ijpds.v3i2.470","title":"Preterm birth, unplanned hospital contact and mortality in infants born to teenage mothers in five countries: a cross-country comparison using linked administrative data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child and Adolescent Health","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Demography; Pediatrics; Public health","score_opus":0.18233229557051672,"score_gpt":0.5498218103733226,"score_spread":0.36748951480280584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809519624","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99109757,0.00002515191,0.0011083083,0.0005785843,0.002251757,0.00088221923,0.0039956877,0.000012914482,0.0000478177],"genre_scores_gemma":[0.996535,0.00003066658,0.0014197561,0.00078464363,0.00062391296,0.0000025008462,0.0005738339,0.000010262195,0.000019413945],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99734175,0.00010515564,0.0009050332,0.0005628626,0.00066782883,0.00041736828],"domain_scores_gemma":[0.9981038,0.00023208027,0.0005402838,0.00051029725,0.00041570727,0.0001978481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00264242,0.00013757772,0.00023500781,0.00034763577,0.00065551884,0.0002438107,0.0013377327,0.00007111935,0.000033540655],"category_scores_gemma":[0.0014479483,0.00012280594,0.000012553968,0.00033415257,0.00021520049,0.0027799793,0.0006496225,0.00040611872,0.000005457349],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033097586,0.00006477495,0.9952865,0.000023930193,0.00001046655,0.00000825545,0.0031969012,0.000055636,0.000070254224,0.0003809489,0.00025715426,0.00031417445],"study_design_scores_gemma":[0.0013303708,0.00011238975,0.93143374,0.0007033139,0.0000047780054,0.00000919651,0.001352341,0.063104756,0.0000055399037,0.00020097614,0.0016062554,0.00013632413],"about_ca_topic_score_codex":0.002485562,"about_ca_topic_score_gemma":0.008372319,"teacher_disagreement_score":0.06385277,"about_ca_system_score_codex":0.00044299083,"about_ca_system_score_gemma":0.00083467737,"threshold_uncertainty_score":0.5041787},"labels":[],"label_agreement":null},{"id":"W2811987522","doi":"10.23889/ijpds.v3i1.448","title":"Identifying Cases of Sleep Disorders through International Classification of Diseases (ICD) Codes in Administrative Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Sleep and related disorders","field":"Psychology","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Narcolepsy; Diagnosis code; Medicine; Insomnia; Sleep disorder; Cohort; Obstructive sleep apnea; Population; Psychiatry; Medical record; Pediatrics; Internal medicine; Neurology","score_opus":0.22090343225230363,"score_gpt":0.49578043452060044,"score_spread":0.2748770022682968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2811987522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88846177,0.00064314983,0.08504817,0.00224424,0.014889101,0.0006479661,0.0053436034,0.000048834398,0.0026731666],"genre_scores_gemma":[0.9947815,0.00013946355,0.0030339535,0.000042174015,0.00024399409,0.0000066974344,0.0016960058,0.000012005726,0.00004424072],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977982,0.00006452346,0.0007523863,0.00048794234,0.0007071535,0.00018976085],"domain_scores_gemma":[0.99763733,0.0002655914,0.000744517,0.0006803975,0.00061249937,0.000059659564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079285644,0.00011361842,0.00015674846,0.0004497009,0.00015519645,0.000104453306,0.0032810606,0.000061029394,0.0001947553],"category_scores_gemma":[0.0013925083,0.00010431135,0.000045579778,0.00042761603,0.00066115055,0.0028011436,0.00042847596,0.00012928095,0.000008393605],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016034974,0.0020650974,0.7764629,0.00002657491,0.001011606,0.000017751316,0.0045349086,0.00038524676,0.002669242,0.08945457,0.0054604504,0.11630816],"study_design_scores_gemma":[0.002842805,0.0002594794,0.9188805,0.00021862659,0.00013753267,0.000115009076,0.0059924964,0.04825184,0.00025647387,0.017048834,0.0056818826,0.0003144721],"about_ca_topic_score_codex":0.00067826244,"about_ca_topic_score_gemma":0.0006859487,"teacher_disagreement_score":0.14241765,"about_ca_system_score_codex":0.00007814856,"about_ca_system_score_gemma":0.00014007385,"threshold_uncertainty_score":0.6097082},"labels":[],"label_agreement":null},{"id":"W2824096056","doi":"10.23889/ijpds.v3i1.418","title":"Childbirth-Related Hospital Burden by Socioeconomic Status in a Universal Health Care Setting","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal and Perinatal Health Interventions","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada; McGill University","funders":"","keywords":"Childbirth; Socioeconomic status; Medicine; Demography; Residence; Context (archaeology); Population; Health care; Community health; Public health; Pregnancy; Environmental health; Geography; Nursing","score_opus":0.02274092714144733,"score_gpt":0.3955343312750525,"score_spread":0.3727934041336052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2824096056","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9858896,0.00020406368,0.0005659366,0.008712991,0.0025778853,0.00029957364,0.0014904538,0.000021995274,0.0002374685],"genre_scores_gemma":[0.9959725,0.00005437601,0.0016737306,0.00035384548,0.0004444955,0.0000029111104,0.0010168997,0.0000094501065,0.00047180481],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984364,0.000023934714,0.000519971,0.00030301214,0.000392334,0.00032433838],"domain_scores_gemma":[0.99888587,0.000023204248,0.0003141682,0.00019382422,0.00036052748,0.00022243346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000653166,0.00008921841,0.00013172984,0.00029704822,0.00034687613,0.00012417305,0.0005969318,0.000035444948,0.0003226943],"category_scores_gemma":[0.00013977247,0.00008406408,0.000048378693,0.000120593235,0.00014942372,0.0011012207,0.0001730779,0.00019007563,0.000031993135],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080776855,0.00038857985,0.7019538,0.0002760063,0.00015573729,0.000057523135,0.010357648,0.0001440632,0.0005833311,0.0069533996,0.02094146,0.25738063],"study_design_scores_gemma":[0.0046800836,0.0014661833,0.7849982,0.0006619917,0.000014041318,0.00048298953,0.0025362826,0.027693858,0.000108870205,0.00101889,0.176008,0.0003306091],"about_ca_topic_score_codex":0.0021426075,"about_ca_topic_score_gemma":0.0002509102,"teacher_disagreement_score":0.25705004,"about_ca_system_score_codex":0.0008472244,"about_ca_system_score_gemma":0.00044762847,"threshold_uncertainty_score":0.35332763},"labels":[],"label_agreement":null},{"id":"W2883238867","doi":"10.23889/ijpds.v3i1.445","title":"Coding reliability and agreement of international classification of disease, 10th revision (ICD-10) codes in emergency department data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Audit; Coding (social sciences); Emergency department; Diagnosis code; ICD-10; Medicine; Medical emergency; Reliability (semiconductor); Computer science; Statistics; Nursing; Environmental health; Business; Mathematics; Population","score_opus":0.3808662722987242,"score_gpt":0.5501127744964156,"score_spread":0.16924650219769138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883238867","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9307145,0.00012649586,0.048700172,0.008201267,0.007249844,0.0011449308,0.0027903677,0.000019977264,0.001052448],"genre_scores_gemma":[0.9913116,0.00072628015,0.0053656427,0.00008956822,0.00040582722,0.000008465869,0.0019996022,0.0000043552113,0.00008864196],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966888,0.000121752346,0.0015080887,0.00033705108,0.0011402996,0.000204047],"domain_scores_gemma":[0.9963851,0.00022564991,0.0011687718,0.0006100509,0.0014430581,0.00016734372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070484867,0.000083516716,0.00016024213,0.0003598506,0.00039968715,0.00002549635,0.0015711768,0.000049331687,0.0004371392],"category_scores_gemma":[0.0056380476,0.000070870025,0.000019347266,0.00024490277,0.00018910882,0.001947177,0.0007164277,0.0001771896,0.000008229936],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087223866,0.00019931339,0.9280121,0.00035659954,0.00002632091,5.415729e-7,0.0008591519,0.000092490154,0.000656239,0.011708558,0.018900635,0.038315844],"study_design_scores_gemma":[0.0006833974,0.000077943434,0.7573522,0.0005803749,0.000013550909,0.0000013281023,0.00027488623,0.21579759,0.000019665235,0.001669739,0.023450175,0.00007919441],"about_ca_topic_score_codex":0.00016165018,"about_ca_topic_score_gemma":0.00016256212,"teacher_disagreement_score":0.2157051,"about_ca_system_score_codex":0.00024997236,"about_ca_system_score_gemma":0.0003971375,"threshold_uncertainty_score":0.67496765},"labels":[],"label_agreement":null},{"id":"W2888676651","doi":"10.23889/ijpds.v3i1.436","title":"A Metadata Manifesto: The Need for Global Health Metadata","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Metadata; Health data; Manifesto; Work (physics); Population health; Data quality; Health care; Process (computing); Quality (philosophy); Population; Global health; Public health; Computer science; Data science; Business; Environmental health; Medicine; World Wide Web; Political science; Nursing; Engineering","score_opus":0.5205488656453303,"score_gpt":0.6212911584990422,"score_spread":0.10074229285371183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888676651","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007882951,0.00012325791,0.88219506,0.08312874,0.02004131,0.0018948542,0.0037797412,0.00007218155,0.0008819065],"genre_scores_gemma":[0.87138796,0.00021351766,0.06700971,0.041186143,0.011261878,0.00017725736,0.005741312,0.000028914505,0.0029933213],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966512,0.00014999809,0.0010831534,0.00032872736,0.0012235118,0.0005634196],"domain_scores_gemma":[0.99605435,0.0004967846,0.0009771386,0.00070646626,0.0014582863,0.00030700205],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.011187946,0.000116561605,0.00018303221,0.00015155903,0.0041873893,0.00039786746,0.0032329462,0.000061966464,0.00009414133],"category_scores_gemma":[0.0054720496,0.00007604945,0.000049464474,0.00036109987,0.0002326655,0.0057925023,0.0005575941,0.000308663,0.000038720318],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048090288,0.000068555935,0.013340306,0.0001172426,0.00009683951,8.510018e-7,0.0011026689,0.00003689975,0.000024716452,0.49179453,0.39429426,0.09864223],"study_design_scores_gemma":[0.0014004058,0.0002008642,0.040919323,0.00018627277,0.000030367357,0.00005558662,0.00089189305,0.06459828,0.000003553154,0.017146608,0.8744205,0.00014633984],"about_ca_topic_score_codex":0.00062285917,"about_ca_topic_score_gemma":0.0007860892,"teacher_disagreement_score":0.863505,"about_ca_system_score_codex":0.0005894188,"about_ca_system_score_gemma":0.001863063,"threshold_uncertainty_score":0.997109},"labels":[],"label_agreement":null},{"id":"W2889191855","doi":"10.23889/ijpds.v3i1.697","title":"The International Population Data Linkage Network – Banff and Beyond","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of Calgary","funders":"","keywords":"Context (archaeology); Population; NOMINATE; Public relations; Library science; Computer science; Political science; Sociology; Geography","score_opus":0.29041916002824336,"score_gpt":0.5082813043779627,"score_spread":0.21786214434971934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889191855","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18229854,0.00073419727,0.51363754,0.14157549,0.13624991,0.0022121451,0.010168823,0.00023239342,0.012890946],"genre_scores_gemma":[0.9638779,0.0002471759,0.022553233,0.0023720565,0.0055786995,0.0000068423433,0.003661908,0.000016155418,0.0016859922],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9938445,0.00012351527,0.0010504577,0.00093639235,0.003687006,0.00035812173],"domain_scores_gemma":[0.99455684,0.001048,0.000806346,0.0020393217,0.0013738703,0.00017562143],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.020140694,0.00014681245,0.00015201903,0.00034032768,0.0019856,0.0055129654,0.014395122,0.00004721017,0.00014361783],"category_scores_gemma":[0.011167107,0.00009935734,0.00004037863,0.00059321075,0.00052282633,0.008836553,0.0055916724,0.00018295737,0.00006691282],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020425075,0.000060081973,0.040249657,0.0000019038482,0.00009636379,0.000005542727,0.00015713582,0.0003535382,0.000072975214,0.16600674,0.29818517,0.49460664],"study_design_scores_gemma":[0.0003788135,0.00004016032,0.121639766,0.000019235713,0.00001518727,0.000046111778,0.00021302729,0.15693551,0.000005044609,0.0919166,0.6286447,0.00014582336],"about_ca_topic_score_codex":0.0002591896,"about_ca_topic_score_gemma":0.0013568628,"teacher_disagreement_score":0.7815794,"about_ca_system_score_codex":0.00011579977,"about_ca_system_score_gemma":0.000107319545,"threshold_uncertainty_score":0.99931365},"labels":[],"label_agreement":null},{"id":"W2889599455","doi":"10.23889/ijpds.v3i4.982","title":"Canadian Approaches to Optimizing Quality of Administrative Data for Health System Use, Research, and Linkage","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information; University of Calgary","funders":"","keywords":"Data quality; Quality (philosophy); Information quality; Quality management; Terminology; Health care; Data science; Information system; Medicine; Computer science; Business; Political science; Marketing","score_opus":0.9507252480945603,"score_gpt":0.6853792962005697,"score_spread":0.2653459518939906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889599455","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2716209,0.000093648036,0.5670593,0.1111687,0.011124082,0.006772118,0.030138424,0.00008010444,0.0019427324],"genre_scores_gemma":[0.9312311,0.000014763883,0.065511994,0.00087849767,0.000812776,0.000028351611,0.0013837828,0.0000066597627,0.00013209453],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970786,0.0002261876,0.001009007,0.00033327966,0.00089701434,0.00045593694],"domain_scores_gemma":[0.99552983,0.0010057614,0.0005821085,0.0005800882,0.0016491051,0.0006531087],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.021611724,0.00006817118,0.00017374175,0.0005135376,0.0024132533,0.00013702635,0.0016363297,0.00006290422,0.000011042797],"category_scores_gemma":[0.0086076185,0.000058136575,0.00001129255,0.0002955238,0.00018787413,0.0020650122,0.00047453106,0.0002981882,0.0000051032835],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016916132,0.0001476233,0.096549205,0.0026670555,0.00011809094,0.0000018596347,0.019278493,0.00016471831,0.0001281544,0.6792561,0.1342801,0.06571703],"study_design_scores_gemma":[0.002829329,0.0015629733,0.2512811,0.0038046471,0.00001632728,0.000039165447,0.018970728,0.48880753,0.00003896824,0.004145065,0.22804639,0.00045775415],"about_ca_topic_score_codex":0.03775508,"about_ca_topic_score_gemma":0.06408906,"teacher_disagreement_score":0.675111,"about_ca_system_score_codex":0.00074837886,"about_ca_system_score_gemma":0.0034031288,"threshold_uncertainty_score":0.9997433},"labels":[],"label_agreement":null},{"id":"W2889621795","doi":"10.23889/ijpds.v3i4.685","title":"Childhood Mental Disorders and Subsequent Adverse Outcomes in Early Adulthood: A Population-Based Longitudinal Study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Mental health; Psychiatry; Population; Medicine; Cohort; Hazard ratio; Cohort study; Demography; Psychology; Confidence interval; Environmental health","score_opus":0.05747493910967577,"score_gpt":0.42407636876255184,"score_spread":0.36660142965287607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889621795","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914064,0.000013529291,0.0003403186,0.0048300363,0.002570488,0.000599555,0.00014776333,0.000019919176,0.000072038536],"genre_scores_gemma":[0.9978986,0.000024584147,0.0011937924,0.0004042501,0.00033116672,0.000012759264,0.00008381542,0.0000075424623,0.000043532287],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99747,0.00009595365,0.0004823605,0.00038785825,0.0011778609,0.00038594977],"domain_scores_gemma":[0.9989139,0.00015317409,0.00023489697,0.00021511369,0.00026534058,0.00021756327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002211771,0.00011473286,0.00015424404,0.00039017253,0.0012367076,0.0003687709,0.0010631933,0.000037888938,0.00006166769],"category_scores_gemma":[0.0012979174,0.000103847466,0.00004010204,0.00032145897,0.00024329724,0.0023613418,0.00016023073,0.00012627279,0.0000042432707],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033415068,0.00016763608,0.9903722,0.000001922028,0.000010178211,0.0000015969956,0.0026033903,0.000019971649,4.202366e-7,0.0035086942,0.00003716424,0.0032434498],"study_design_scores_gemma":[0.0010080215,0.000086914224,0.99308634,0.000032955933,0.0000072233165,0.0000021618366,0.002187406,0.0014419691,4.2678235e-7,0.0011207354,0.0009050694,0.000120797355],"about_ca_topic_score_codex":0.033020034,"about_ca_topic_score_gemma":0.06795499,"teacher_disagreement_score":0.034934953,"about_ca_system_score_codex":0.00038514409,"about_ca_system_score_gemma":0.0003489658,"threshold_uncertainty_score":0.9734192},"labels":[],"label_agreement":null},{"id":"W2889641933","doi":"10.23889/ijpds.v3i4.669","title":"Gaining knowledge of Ontario’s community mental health and addictions system: linking community-based health services data with administrative health data in Toronto, Ontario, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Community Health and Development","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Centre for Addiction and Mental Health","funders":"","keywords":"Mental health; Community health; Addiction; Neighbourhood (mathematics); Health care; Medicine; Business; Psychology; Nursing; Public health; Psychiatry; Political science","score_opus":0.2567628588408797,"score_gpt":0.513017471292901,"score_spread":0.2562546124520213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889641933","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92601043,0.0011835614,0.006705126,0.021090433,0.008643843,0.005014285,0.028768511,0.00011194127,0.0024718978],"genre_scores_gemma":[0.9448011,0.000051440686,0.01558845,0.0044432865,0.00014575783,0.000015049465,0.034871697,0.00001557641,0.00006766623],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9947978,0.0017640073,0.0015600849,0.00039902594,0.00085302716,0.00062600645],"domain_scores_gemma":[0.99389184,0.0007744585,0.0016975331,0.0022620894,0.0007459702,0.0006280931],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.014618618,0.00020110603,0.00044753327,0.00025126446,0.008197791,0.00010632151,0.00507566,0.000052219035,0.00005468705],"category_scores_gemma":[0.00019020046,0.00018420452,0.000011494024,0.0002962567,0.00022437816,0.0023753394,0.0030337633,0.0016215759,8.332867e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00095848023,0.0006996303,0.75962627,0.0022019623,0.00011178397,0.0000018927987,0.20739095,0.000032013802,0.0000024738833,0.0018241489,0.0083186,0.018831793],"study_design_scores_gemma":[0.0038787068,0.0014287352,0.64167273,0.012985408,0.000012995836,0.000083587925,0.16421321,0.024499761,7.910817e-7,0.00009466019,0.15074892,0.00038046495],"about_ca_topic_score_codex":0.9990167,"about_ca_topic_score_gemma":0.99998367,"teacher_disagreement_score":0.14243034,"about_ca_system_score_codex":0.016777273,"about_ca_system_score_gemma":0.088969104,"threshold_uncertainty_score":0.9930934},"labels":[],"label_agreement":null},{"id":"W2889644645","doi":"10.23889/ijpds.v3i4.972","title":"Sociodemographic correlates of cervical cancer screening rates in Calgary, AB: Matched Trend analysis of 2006, 2011 and 2016","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cervical Cancer and HPV Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Demography; Medicine; Ethnic group; Cervical cancer; Trend analysis; Binomial regression; Pap test; Geography; Gerontology; Cervical cancer screening; Logistic regression; Cancer; Statistics","score_opus":0.08673044249527231,"score_gpt":0.4460482696663771,"score_spread":0.35931782717110483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889644645","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932596,0.000626605,0.0039251293,0.0011065822,0.00032587702,0.0001372568,0.00045477512,0.000004585727,0.00015957108],"genre_scores_gemma":[0.99743676,0.0004308617,0.0016773076,0.000058270725,0.00013225,0.0000031621676,0.00019435893,0.0000047627123,0.00006225127],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983501,0.000021824026,0.00045898042,0.00023966783,0.0007618604,0.00016760858],"domain_scores_gemma":[0.99860275,0.000114866016,0.00022032492,0.00018392557,0.0007618128,0.00011635144],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0010487871,0.00006931183,0.00024774013,0.0010742175,0.00008776577,0.000042304342,0.00048988697,0.000042704945,0.0009915386],"category_scores_gemma":[0.00023583916,0.000054601074,0.000067596804,0.00080772827,0.00044246842,0.000539646,0.00017969807,0.0001337249,6.8856974e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038856306,0.000051677584,0.9675672,0.000013330824,0.00019773994,0.000001473271,0.00011388346,0.00006830935,0.0008477877,0.00031979653,0.00024422206,0.030185984],"study_design_scores_gemma":[0.00077181065,0.00008199993,0.8840544,0.00004936211,0.00013759622,0.000007929666,0.000057932564,0.11409152,0.00022443855,0.00036309872,0.00011210226,0.000047762238],"about_ca_topic_score_codex":0.003090493,"about_ca_topic_score_gemma":0.0027716004,"teacher_disagreement_score":0.11402321,"about_ca_system_score_codex":0.000058715083,"about_ca_system_score_gemma":0.00015158883,"threshold_uncertainty_score":0.9999217},"labels":[],"label_agreement":null},{"id":"W2889665512","doi":"10.23889/ijpds.v3i4.941","title":"Approaches to Capacity Building for Machine Learning and Artificial Intelligence Applications in Health","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Vector Institute","funders":"","keywords":"General partnership; Artificial intelligence; Medical education; Health care; Public relations; Management; Political science; Operations research; Engineering; Psychology; Computer science; Medicine; Business; Finance","score_opus":0.6205560122191686,"score_gpt":0.5330517585959609,"score_spread":0.08750425362320768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889665512","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29086182,0.000066825836,0.6931819,0.01371775,0.0009983409,0.0010418404,0.000087642664,0.000020209702,0.00002372077],"genre_scores_gemma":[0.91414183,0.000033039072,0.08435652,0.00032136647,0.0008936853,0.00005010263,0.00016871913,0.000008338844,0.000026398884],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99837047,0.000024398945,0.0005957613,0.0003885867,0.00036329613,0.00025746145],"domain_scores_gemma":[0.9987104,0.00019136019,0.00021420619,0.00017913294,0.00048407106,0.0002208629],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024666656,0.00008487941,0.00013351947,0.00047739106,0.000618522,0.00017617106,0.00042375588,0.000034400087,0.0000124363805],"category_scores_gemma":[0.0018577145,0.00007876395,0.000023891906,0.00041626536,0.00015453596,0.000637769,0.00010498796,0.00016037318,0.0000032917471],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003116734,0.0001881697,0.1019748,0.00007013145,0.000016883083,4.1199715e-7,0.0021216248,0.0007004886,0.0014070325,0.092888765,0.00010791115,0.8002121],"study_design_scores_gemma":[0.00016872,0.0012716778,0.037767842,0.00046160218,0.000026869508,0.00021099354,0.003341455,0.76902896,0.009465744,0.12664789,0.051174827,0.00043341206],"about_ca_topic_score_codex":0.0008261288,"about_ca_topic_score_gemma":0.00070272177,"teacher_disagreement_score":0.7997787,"about_ca_system_score_codex":0.0002734864,"about_ca_system_score_gemma":0.00027030252,"threshold_uncertainty_score":0.47572336},"labels":[],"label_agreement":null},{"id":"W2889669580","doi":"10.23889/ijpds.v3i4.996","title":"Linking medical licensing examination scores with longitudinal physician practice data using a privacy preserving protocol","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Malpractice and Liability Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Medical Council of Canada; College of Physicians and Surgeons of Ontario","funders":"","keywords":"Licensure; Cohort; Encryption; Protocol (science); Competence (human resources); Credential; Medical record; Information privacy; Privacy law; Key (lock); Internet privacy; Computer security; Computer science; Business; Medicine; Medical education; Psychology; Privacy policy","score_opus":0.3491210849388082,"score_gpt":0.5967497560950241,"score_spread":0.2476286711562159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889669580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48777637,0.000029754166,0.41273147,0.042456154,0.009382934,0.043755203,0.00036302183,0.0002374905,0.003267585],"genre_scores_gemma":[0.8816067,0.00000783262,0.10548663,0.0022327441,0.009303374,0.00067293504,0.0005771249,0.00003406589,0.000078598256],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9942905,0.00047378638,0.0008554688,0.00073507335,0.0031579065,0.00048732062],"domain_scores_gemma":[0.99232787,0.0017129256,0.0012636122,0.0012283358,0.0031612916,0.0003059541],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.012666305,0.0001583643,0.00019267536,0.00028905974,0.0021076219,0.00041305783,0.0042137294,0.00010845801,0.00028600838],"category_scores_gemma":[0.037797302,0.0001207954,0.000020459782,0.0005158404,0.00042006926,0.0129949255,0.0023432123,0.0007472961,0.000023945535],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0039763427,0.0016761775,0.6364996,0.0008304974,0.00045094854,0.00018792601,0.011559485,0.00030682771,0.0025981558,0.014538093,0.012861034,0.31451494],"study_design_scores_gemma":[0.002462397,0.000334786,0.11548166,0.0039138324,0.00012050796,0.0002899605,0.0023842293,0.6064069,0.00006123721,0.0010394702,0.26710692,0.0003980414],"about_ca_topic_score_codex":0.0006596293,"about_ca_topic_score_gemma":0.00035197756,"teacher_disagreement_score":0.60610014,"about_ca_system_score_codex":0.00031120214,"about_ca_system_score_gemma":0.0016876461,"threshold_uncertainty_score":0.9991915},"labels":[],"label_agreement":null},{"id":"W2889670592","doi":"10.23889/ijpds.v3i4.983","title":"Linking First Nations data to administrative health data within Manitoba","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"First Nations Health and Social Secretariat of Manitoba","funders":"","keywords":"Mandate; Equity (law); Health care; Political science; Business; Public administration","score_opus":0.4465527572805304,"score_gpt":0.5707038364821475,"score_spread":0.12415107920161711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889670592","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2310652,0.0003453372,0.2656374,0.25387472,0.14420624,0.010330903,0.08410704,0.0004043021,0.01002886],"genre_scores_gemma":[0.935681,0.00010442183,0.043997694,0.0044113123,0.005236593,0.000027998007,0.010219261,0.000021625807,0.00030009987],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966274,0.000108215456,0.0009314244,0.00077987596,0.0008326171,0.00072049536],"domain_scores_gemma":[0.9949006,0.000554,0.00079719245,0.0017876879,0.0017107844,0.00024975513],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.007050596,0.00013157235,0.00019114342,0.00041606656,0.014824545,0.00019693507,0.007867155,0.000060570233,0.00013633871],"category_scores_gemma":[0.0059136846,0.00011637836,0.000015611147,0.0004931456,0.00018379964,0.0030166686,0.006215125,0.00035381145,0.00017395869],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065369706,0.0005803143,0.3636022,0.00018447581,0.00043121525,0.00002918911,0.06057346,0.0004630393,0.00011688265,0.08233418,0.46761698,0.023414362],"study_design_scores_gemma":[0.0010933105,0.0005458686,0.10710466,0.00055733393,0.000033034834,0.00010057901,0.020668764,0.058768757,0.000004893025,0.0017579703,0.80895615,0.00040867832],"about_ca_topic_score_codex":0.0041432455,"about_ca_topic_score_gemma":0.5278449,"teacher_disagreement_score":0.7046158,"about_ca_system_score_codex":0.0007376705,"about_ca_system_score_gemma":0.0022993821,"threshold_uncertainty_score":0.9975008},"labels":[],"label_agreement":null},{"id":"W2889674305","doi":"10.23889/ijpds.v3i4.796","title":"A Longitudinal Analysis of the Families First Screening Program in Manitoba, Canada: Cleaning, Validating and Linking via Health Registry Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Grief, Bereavement, and Mental Health","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Medicine; Public health; Environmental health; Demography; Medical emergency; Family medicine; Pediatrics; Nursing","score_opus":0.1670237997446483,"score_gpt":0.44308947969377155,"score_spread":0.27606567994912323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889674305","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9853606,0.00007987886,0.009983574,0.0013054681,0.0020342912,0.000350559,0.00076362165,0.000009464875,0.00011253191],"genre_scores_gemma":[0.99294007,0.000020806781,0.0059075607,0.00021331302,0.00023733018,0.00000429322,0.00065036124,0.000005719417,0.000020559002],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997975,0.000055879536,0.0005701755,0.00042456886,0.0007023567,0.00027204887],"domain_scores_gemma":[0.9982494,0.00008535038,0.0007078013,0.0006514893,0.00021350534,0.00009241365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020538399,0.00008726754,0.00015781613,0.00030691404,0.0005993625,0.00013841479,0.0019772542,0.00002361593,0.000017507424],"category_scores_gemma":[0.000216854,0.00007071272,0.000023447044,0.00067511515,0.00020488127,0.00074619264,0.0007057127,0.00015396347,2.4488293e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034699828,0.000051524163,0.944288,0.000015244085,0.000102069986,0.0000026083735,0.00040999334,0.0000786558,0.000012093415,0.0007774361,0.0005489099,0.053678725],"study_design_scores_gemma":[0.00031337992,0.00006204334,0.9570037,0.0001829316,0.000041862473,0.000046023586,0.0011871468,0.039175056,0.0000076028073,0.000093709416,0.0018170611,0.000069481364],"about_ca_topic_score_codex":0.49707454,"about_ca_topic_score_gemma":0.8930471,"teacher_disagreement_score":0.39597258,"about_ca_system_score_codex":0.00026345023,"about_ca_system_score_gemma":0.00032794088,"threshold_uncertainty_score":0.50627446},"labels":[],"label_agreement":null},{"id":"W2889677026","doi":"10.23889/ijpds.v3i4.957","title":"The Use of Long-Acting Injectable Antipsychotic Therapy for Schizophrenia","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Schizophrenia research and treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; Alberta Health Services","funders":"","keywords":"Medicine; Antipsychotic; Cohort; Comorbidity; Psychiatry; Schizophrenia (object-oriented programming); Mental health; Emergency medicine; Internal medicine","score_opus":0.19862573714412488,"score_gpt":0.44958122477728946,"score_spread":0.25095548763316455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889677026","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9719297,0.00013263649,0.022358693,0.002567607,0.0021271252,0.00066934177,0.00017837352,0.0000135834825,0.000022888778],"genre_scores_gemma":[0.9636392,0.00014702746,0.03516516,0.00008389131,0.000662319,0.000011339678,0.00013621722,0.000008815613,0.00014604877],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9984819,0.000016788,0.00030646333,0.00022424712,0.00074749894,0.00022308019],"domain_scores_gemma":[0.99765086,0.0003232469,0.00022818467,0.00037659338,0.0013106772,0.00011041295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009938648,0.00007316019,0.00009959697,0.00019072468,0.0006208613,0.0003451129,0.00075706374,0.000020091844,0.000020746536],"category_scores_gemma":[0.0018504147,0.00004469681,0.00005893563,0.0002284563,0.0002524689,0.0012164144,0.00009337743,0.00008326915,0.0000032487533],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.038259204,0.00032790957,0.0964058,0.00001220466,0.00036436945,0.000009577523,0.000096417636,0.00006825974,0.006659868,0.008753248,0.0047424682,0.8443007],"study_design_scores_gemma":[0.01588394,0.0025484092,0.8155646,0.00033058733,0.0000764795,0.0006908421,0.000089297384,0.101439655,0.014252463,0.009718196,0.039134018,0.00027156144],"about_ca_topic_score_codex":0.00007025804,"about_ca_topic_score_gemma":0.00011819615,"teacher_disagreement_score":0.8440291,"about_ca_system_score_codex":0.00008738063,"about_ca_system_score_gemma":0.00035259023,"threshold_uncertainty_score":0.47752258},"labels":[],"label_agreement":null},{"id":"W2889680530","doi":"10.23889/ijpds.v3i4.740","title":"Where it’s at - linking data geographically.","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Geocoding; Geographic information system; Geospatial analysis; Data science; Presentation (obstetrics); Location; Scale (ratio); Geography; Computer science; Data mining; Cartography; Medicine","score_opus":0.10069259066167668,"score_gpt":0.43354955170196735,"score_spread":0.33285696104029067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889680530","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.797289,0.00095068035,0.0759392,0.057758294,0.0298393,0.0019333309,0.0300852,0.00047915181,0.0057258015],"genre_scores_gemma":[0.9594103,0.00020772048,0.023397537,0.0017703952,0.0027500326,0.0000034276338,0.011933594,0.000021233636,0.0005057312],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969807,0.000026578497,0.0004920554,0.00066910556,0.0015328899,0.00029864936],"domain_scores_gemma":[0.996495,0.00008585377,0.00031993157,0.0016209387,0.0011919746,0.00028627974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020184866,0.00012252187,0.0001592059,0.00034321542,0.0005443804,0.00035773084,0.004006613,0.00004429374,0.0004008623],"category_scores_gemma":[0.00183136,0.00010513383,0.000048767462,0.00038986656,0.00041491023,0.0029934247,0.0022141407,0.00016357841,0.00008875634],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068247004,0.00019872609,0.81280005,0.000035238405,0.0001790903,0.00007155259,0.00007683283,0.000024835674,0.0037894296,0.0023221574,0.1321077,0.047711916],"study_design_scores_gemma":[0.0011944735,0.000107068525,0.38337347,0.00031788013,0.00005418199,0.0006133033,0.00002590575,0.055255923,0.000056507033,0.00086231495,0.55794036,0.00019858989],"about_ca_topic_score_codex":0.000071471775,"about_ca_topic_score_gemma":0.00044757372,"teacher_disagreement_score":0.42942655,"about_ca_system_score_codex":0.00018204357,"about_ca_system_score_gemma":0.00028713213,"threshold_uncertainty_score":0.7445351},"labels":[],"label_agreement":null},{"id":"W2889680783","doi":"10.23889/ijpds.v3i4.762","title":"Predicting health care utilization using CIHI's Population Grouping Methodology","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Health care; Population; Population health; Business; Medicine; Environmental health; Economics","score_opus":0.47714580563510706,"score_gpt":0.5846272929485187,"score_spread":0.10748148731341162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889680783","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6538766,0.00041480016,0.30690753,0.011233123,0.025569245,0.00082958944,0.00032237047,0.0001386534,0.0007080911],"genre_scores_gemma":[0.94568014,0.000081350074,0.049227096,0.0015394839,0.00307921,0.000002680487,0.00033910983,0.0000106650505,0.000040240542],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99718297,0.00026281975,0.0006017507,0.00037187416,0.001089557,0.0004910486],"domain_scores_gemma":[0.9975806,0.00023622623,0.0005799997,0.00023942029,0.0011262412,0.0002374989],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0056249136,0.00009538072,0.00015743694,0.00037297764,0.0034478065,0.0005149539,0.0012667096,0.00006557291,0.000071380695],"category_scores_gemma":[0.0042367354,0.00009645838,0.000043444645,0.0004496031,0.00025941624,0.0033266193,0.00020953047,0.00012956404,0.0000022700651],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006932661,0.000029287927,0.78862876,0.0000355247,0.000024859397,0.0000015115498,0.011963722,0.0005380402,0.000044022316,0.08465536,0.0007698226,0.11323975],"study_design_scores_gemma":[0.0008698262,0.00013269423,0.80124956,0.00035856536,0.000029476843,0.000061730614,0.015936032,0.110756874,0.00003524227,0.008260817,0.061897036,0.00041212759],"about_ca_topic_score_codex":0.026900277,"about_ca_topic_score_gemma":0.012066975,"teacher_disagreement_score":0.29180357,"about_ca_system_score_codex":0.001038599,"about_ca_system_score_gemma":0.00083497935,"threshold_uncertainty_score":0.9978496},"labels":[],"label_agreement":null},{"id":"W2889692736","doi":"10.23889/ijpds.v3i4.707","title":"Is Participation in Out-of-School Programs Linked to Students’ Health, Educational and Social Outcomes?","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Youth Development and Social Support","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Receipt; Graduation (instrument); Population; Medical education; Socioeconomic status; Psychology; Medicine; Gerontology; Environmental health","score_opus":0.24561788008704533,"score_gpt":0.5530593177296763,"score_spread":0.307441437642631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889692736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9651725,0.000005172097,0.00069049327,0.03032061,0.0030376608,0.00043318793,0.000056390872,0.000009706921,0.00027424187],"genre_scores_gemma":[0.9943099,0.000010398528,0.0033161193,0.00102421,0.0007505229,0.000015751275,0.000113549686,0.0000046059426,0.00045493958],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975693,0.00005784111,0.00049516815,0.0002549486,0.0013517033,0.00027104263],"domain_scores_gemma":[0.9986612,0.000053668547,0.0002967349,0.00009969702,0.0007012392,0.00018742304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031988763,0.000070179885,0.00012851495,0.00027886956,0.0008322224,0.00035900457,0.0011091485,0.000041072195,0.0001079875],"category_scores_gemma":[0.00097191514,0.00006946924,0.000027201853,0.00033020147,0.00027759114,0.0013724255,0.00019902106,0.000079662896,0.0000131229735],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019781872,0.000083566214,0.9564219,0.0000019379381,0.000010597886,1.468129e-7,0.019808192,4.4077035e-7,0.000010362227,0.0065605524,0.00077114924,0.016311374],"study_design_scores_gemma":[0.00028092568,0.000037334263,0.98537165,0.000022186565,0.0000031851175,3.2570898e-7,0.0007700338,0.00006257409,0.0000018540611,0.0023922746,0.010979505,0.000078177436],"about_ca_topic_score_codex":0.0011506263,"about_ca_topic_score_gemma":0.004617911,"teacher_disagreement_score":0.0292964,"about_ca_system_score_codex":0.0003321831,"about_ca_system_score_gemma":0.00091624603,"threshold_uncertainty_score":0.6400866},"labels":[],"label_agreement":null},{"id":"W2889696671","doi":"10.23889/ijpds.v3i4.877","title":"Ensemble-based Classification Models for Predicting Post-Operative Mortality Risk in Coronary Artery Disease","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cardiac, Anesthesia and Surgical Outcomes","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Medicine; Receiver operating characteristic; Coronary artery disease; Logistic regression; Internal medicine; Cardiology; Dialysis; Cardiac catheterization; Disease; Emergency medicine","score_opus":0.11620499603873656,"score_gpt":0.4170348411775644,"score_spread":0.3008298451388278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889696671","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86210537,0.000020365282,0.13356459,0.001845164,0.0010333614,0.000619709,0.00063350034,0.000020785272,0.00015716207],"genre_scores_gemma":[0.9899647,0.000013060121,0.00787363,0.00054004474,0.0005550285,0.00003058213,0.00094940077,0.000009763258,0.0000637738],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981181,0.000047712743,0.00046729174,0.00038273237,0.0007799702,0.00020420211],"domain_scores_gemma":[0.9977636,0.00041066954,0.00023467523,0.00033717253,0.0010498844,0.00020401967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001784249,0.00010604409,0.0001992727,0.0002782376,0.00030571487,0.00015934011,0.00046490735,0.00003765123,0.00001795622],"category_scores_gemma":[0.002128234,0.0000873453,0.00012363117,0.00017730238,0.00017826082,0.0015689991,0.00005648789,0.000120490426,0.000002862274],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019106535,0.00015930815,0.97361076,0.000011919273,0.00005485235,0.00002673708,0.00013145882,0.0024424456,0.00061244454,0.0068467837,0.000112749876,0.01407989],"study_design_scores_gemma":[0.0009976167,0.000078196004,0.5676528,0.00005044754,0.00004020274,0.000038564467,0.000046758247,0.42958233,0.000024144914,0.00089855085,0.00052956125,0.000060779006],"about_ca_topic_score_codex":0.00007667194,"about_ca_topic_score_gemma":0.00009687792,"teacher_disagreement_score":0.42713988,"about_ca_system_score_codex":0.00021734562,"about_ca_system_score_gemma":0.00041559548,"threshold_uncertainty_score":0.35618383},"labels":[],"label_agreement":null},{"id":"W2889701131","doi":"10.23889/ijpds.v3i4.917","title":"Evidence from an Applied Research Health Question (AHRQ): Healthcare utilization of HIV patients before and after admission to Casey House, a specialized HIV hospital","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"HIV/AIDS Research and Interventions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Casey House","funders":"","keywords":"Medicine; Health care; Specialty; Family medicine; Emergency department; Medical prescription; Medical emergency; Emergency medicine; Nursing","score_opus":0.17714679864104355,"score_gpt":0.5243793711720098,"score_spread":0.3472325725309663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889701131","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9669376,0.00009271742,0.019907039,0.010355504,0.00048129735,0.0009945354,0.0011769722,0.000025078858,0.000029237639],"genre_scores_gemma":[0.9895211,0.00011203112,0.008118293,0.00018568736,0.00071989454,0.000024061548,0.0011335042,0.000017525237,0.00016790103],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9965273,0.00015027245,0.00060817663,0.00050711085,0.001851142,0.00035598298],"domain_scores_gemma":[0.9956076,0.00007794386,0.00026171113,0.00043635792,0.0029250851,0.00069129537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027044949,0.00010628659,0.00018493357,0.0007540381,0.00046550267,0.00022115922,0.00068633887,0.000050746843,0.00016247835],"category_scores_gemma":[0.003585863,0.00009149417,0.000038416438,0.00053342077,0.00026726144,0.0018713686,0.00035115654,0.00021379409,0.000016989834],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003122624,0.000643978,0.7545634,0.00008684616,0.000039883722,0.000007663968,0.0032392426,0.000007429781,0.0013181819,0.0015390436,0.01841028,0.21702145],"study_design_scores_gemma":[0.0013345891,0.0047659273,0.9728034,0.0019295131,0.000011407255,0.000017890543,0.00032325817,0.014188505,0.000513658,0.0013476647,0.0026477044,0.000116475734],"about_ca_topic_score_codex":0.0014046372,"about_ca_topic_score_gemma":0.0024926907,"teacher_disagreement_score":0.21824002,"about_ca_system_score_codex":0.00041864402,"about_ca_system_score_gemma":0.000589598,"threshold_uncertainty_score":0.4292872},"labels":[],"label_agreement":null},{"id":"W2889703278","doi":"10.23889/ijpds.v3i4.834","title":"Use of linked data to assess the impact of out-of-hospital deaths on 30-day mortality indicators","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Medicine; Mortality rate; Emergency medicine; Myocardial infarction; Stroke (engine); Medical emergency; Database; Demography; Internal medicine","score_opus":0.4662346308291237,"score_gpt":0.48637581775105604,"score_spread":0.02014118692193234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889703278","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9708496,0.00001182598,0.018771794,0.0014199313,0.0024766603,0.00026651987,0.006016643,0.0000036704398,0.00018336144],"genre_scores_gemma":[0.99831104,0.000021724489,0.0011264071,0.00010071998,0.00024068725,0.0000019219692,0.00017520669,0.0000049185724,0.000017347142],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99860835,0.00002044673,0.0007236376,0.00027303325,0.00023058099,0.00014392237],"domain_scores_gemma":[0.99778354,0.00012344071,0.0008978059,0.00085104146,0.00026169245,0.000082469465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030688252,0.00006765829,0.00015957795,0.0004174023,0.00010765034,0.000095475116,0.0025247356,0.000025877293,0.000050362967],"category_scores_gemma":[0.002209095,0.000052771484,0.00004970371,0.00028645605,0.00015454054,0.0013104455,0.00057773327,0.000076124124,0.000010253948],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005451689,0.00033494897,0.724442,0.000017877694,0.0002606321,9.46989e-7,0.00093745365,0.0012370275,0.00008397073,0.24602997,0.005211444,0.021389218],"study_design_scores_gemma":[0.00014269867,0.00024103001,0.96694,0.000034949237,0.0000056567537,5.849982e-7,0.000022776198,0.021291874,0.00006551684,0.0036774382,0.007502603,0.000074857],"about_ca_topic_score_codex":0.002903734,"about_ca_topic_score_gemma":0.00012667694,"teacher_disagreement_score":0.24249803,"about_ca_system_score_codex":0.0001079367,"about_ca_system_score_gemma":0.00010728479,"threshold_uncertainty_score":0.46916288},"labels":[],"label_agreement":null},{"id":"W2889722308","doi":"10.23889/ijpds.v3i4.696","title":"Integrating Ontario Health and Social Services Data to for Research and Policy Development","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Ministry of Children, Community and Social Services","funders":"","keywords":"General partnership; Public relations; Context (archaeology); Health care; Data sharing; Social determinants of health; Knowledge management; Business; Political science; Medicine; Computer science; Geography","score_opus":0.5724768272172017,"score_gpt":0.6576428285707849,"score_spread":0.08516600135358321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889722308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7843414,0.00013536715,0.017458662,0.18713374,0.005576474,0.002569358,0.001985543,0.000049789956,0.0007496689],"genre_scores_gemma":[0.6927961,0.00008302411,0.23398268,0.056667615,0.008194461,0.000103613864,0.00551308,0.000038174025,0.0026212672],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99773633,0.00007482777,0.0005655959,0.00043754355,0.00069653196,0.0004891935],"domain_scores_gemma":[0.99746644,0.0003390016,0.00025908643,0.00030624005,0.0013557902,0.00027342993],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.006946364,0.000079883706,0.00014149587,0.00049052964,0.0046445336,0.00021922117,0.0017074225,0.000043739004,0.000019728184],"category_scores_gemma":[0.00073422777,0.00006713249,0.0000074483282,0.00021847391,0.00013119125,0.0016804719,0.001982842,0.00029298727,0.0000066793446],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00074046035,0.000084162806,0.42232606,0.000452979,0.00006358838,0.0000012648629,0.06662887,6.3278156e-7,0.00024209666,0.060594816,0.10302625,0.34583881],"study_design_scores_gemma":[0.0006131205,0.00018167401,0.20359884,0.00017560131,0.0000022623003,0.000011303183,0.0030914305,0.00097433495,0.0000034958136,0.0039431155,0.7873024,0.00010246387],"about_ca_topic_score_codex":0.022848947,"about_ca_topic_score_gemma":0.20150797,"teacher_disagreement_score":0.6842761,"about_ca_system_score_codex":0.0015359584,"about_ca_system_score_gemma":0.008435262,"threshold_uncertainty_score":0.997186},"labels":[],"label_agreement":null},{"id":"W2889724126","doi":"10.23889/ijpds.v3i4.915","title":"Enhancing description of hospital-conditions with ICD-11 cluster coding: Better codes for monitoring and prevention","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Harm; Computer science; Coding (social sciences); Health care; Cluster (spacecraft); Risk analysis (engineering); Data mining; Medicine; Psychology; Mathematics","score_opus":0.2381497744505419,"score_gpt":0.5060261630757956,"score_spread":0.26787638862525376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889724126","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67181885,0.0000067178325,0.32250556,0.0017840547,0.0031426474,0.00052541646,0.00014190961,0.000015950412,0.000058911726],"genre_scores_gemma":[0.96369314,0.000020035033,0.03433325,0.00020501096,0.0012812453,0.000044661592,0.0002756294,0.0000073678875,0.000139657],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983353,0.000045213477,0.0006466988,0.00019630101,0.00053743337,0.00023903747],"domain_scores_gemma":[0.9973914,0.00025162226,0.00065404736,0.00016746305,0.0014167479,0.000118745935],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0025239289,0.00007625147,0.00011970723,0.00026271478,0.0013069754,0.000080517624,0.0003937368,0.000058961487,0.000030405257],"category_scores_gemma":[0.0011462547,0.000061514285,0.000021125192,0.00013527513,0.00016330412,0.0024970626,0.00010851817,0.00014890311,0.0000030862557],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008372347,0.00017463995,0.9171155,0.00077777123,0.00011205575,8.4249547e-7,0.008809699,0.000119427226,0.012454845,0.02412775,0.010284649,0.02518559],"study_design_scores_gemma":[0.005938083,0.0018082316,0.8592841,0.0048272805,0.00013319215,0.000040434097,0.004117371,0.07900986,0.0037466926,0.021075964,0.019508611,0.00051016925],"about_ca_topic_score_codex":0.00008076869,"about_ca_topic_score_gemma":0.00014815349,"teacher_disagreement_score":0.29187432,"about_ca_system_score_codex":0.0001559019,"about_ca_system_score_gemma":0.00023377083,"threshold_uncertainty_score":0.9999932},"labels":[],"label_agreement":null},{"id":"W2889740895","doi":"10.23889/ijpds.v3i4.1006","title":"Coding Agreement on Identification of Main Resource Use Using ICD-10 and ICD-11","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"ICD-10; Coding (social sciences); Statistics; Schema crosswalk; Computer science; Medicine; Data mining; Mathematics; Geography","score_opus":0.48809845845883676,"score_gpt":0.5607918022996737,"score_spread":0.07269334384083698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889740895","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93638945,0.0000080457685,0.05793133,0.0019485505,0.0026834994,0.00042542195,0.00031896224,0.000017374676,0.00027738922],"genre_scores_gemma":[0.99352086,0.000019545714,0.004357855,0.0007290093,0.0007237968,0.0000046187483,0.00020652021,0.000006082356,0.00043172992],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974662,0.00010521526,0.0009714125,0.00022723433,0.0009825261,0.00024738468],"domain_scores_gemma":[0.99738187,0.00035882022,0.00095408113,0.00030111478,0.0008459052,0.00015823933],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0054432633,0.00007631692,0.000112739435,0.00039630706,0.0013605185,0.000110821464,0.0006603716,0.00006005045,0.00013942935],"category_scores_gemma":[0.0036323196,0.00006584319,0.000018678194,0.00020999744,0.00018243192,0.0017625706,0.000224232,0.00019273863,0.000019024503],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021919126,0.0003806901,0.5420261,0.0007180762,0.00012864583,0.0000072951075,0.012465022,0.0018730983,0.035861216,0.21761784,0.075703785,0.11102633],"study_design_scores_gemma":[0.0016769774,0.00022510294,0.353063,0.0011807668,0.000031877116,0.000034824265,0.0012144847,0.55003643,0.0005377548,0.0021337373,0.08962875,0.00023627125],"about_ca_topic_score_codex":0.00019004307,"about_ca_topic_score_gemma":0.00007117909,"teacher_disagreement_score":0.54816335,"about_ca_system_score_codex":0.00029622324,"about_ca_system_score_gemma":0.000262488,"threshold_uncertainty_score":0.99993956},"labels":[],"label_agreement":null},{"id":"W2889741111","doi":"10.23889/ijpds.v3i4.953","title":"Linking big data for cardiovascular health surveillance – opportunities and challenges using the CANHEART cohort","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bruyère; Women's College Hospital; Statistics Canada; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Cohort; Population; Health care; Environmental health; Population health; Cohort study; Demography; Blood pressure; Gerontology; Internal medicine","score_opus":0.4253740266729182,"score_gpt":0.43623095273892465,"score_spread":0.010856926066006467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889741111","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44687113,0.09939597,0.3242007,0.081585936,0.03559076,0.005145834,0.0069485144,0.0001304268,0.000130736],"genre_scores_gemma":[0.94715863,0.03305518,0.010183571,0.0009965226,0.006795187,0.000010041998,0.0017409115,0.000026344962,0.00003358997],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.997823,0.00006361505,0.00037679987,0.00044479224,0.0010051903,0.00028660818],"domain_scores_gemma":[0.99758476,0.00011512764,0.00020517714,0.0010719188,0.0008099602,0.00021307926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0076391213,0.00010175329,0.00025908925,0.00018710202,0.0009221096,0.00018826628,0.00095242914,0.000034662462,0.0000021323528],"category_scores_gemma":[0.0008528962,0.000070466835,0.000113761496,0.00011407829,0.0002572922,0.0007321639,0.000380663,0.000117966374,3.1774675e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023687282,0.000042169002,0.08829068,0.00019347292,0.0010566341,0.000010837127,0.0003770831,0.0001572851,0.00004403828,0.0014529024,0.0017999373,0.9063381],"study_design_scores_gemma":[0.0010779316,0.00013307146,0.19611943,0.00021456422,0.00013306946,0.0015053758,0.0004509944,0.049890265,0.000008622706,0.00023691908,0.75007135,0.00015842752],"about_ca_topic_score_codex":0.0009232735,"about_ca_topic_score_gemma":0.00046098582,"teacher_disagreement_score":0.90617967,"about_ca_system_score_codex":0.0001535368,"about_ca_system_score_gemma":0.00089047104,"threshold_uncertainty_score":0.7092215},"labels":[],"label_agreement":null},{"id":"W2889743896","doi":"10.23889/ijpds.v3i4.991","title":"Linking primary care EMR data and administrative data in Alberta, Canada: experiences, challenges, and potential solutions","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; University of Calgary","funders":"","keywords":"Custodians; Analytics; Health care; Data collection; Medical record; Medical emergency; Medicine; Computer science; Data science; Political science","score_opus":0.37580310792389104,"score_gpt":0.4723326321179541,"score_spread":0.09652952419406308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889743896","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71553254,0.009405453,0.12930231,0.054867405,0.03223701,0.0026838817,0.04843877,0.00006943218,0.007463193],"genre_scores_gemma":[0.9879991,0.00034990988,0.0057918527,0.00029408865,0.00043881274,0.0000041828807,0.005024033,0.0000048247953,0.00009321016],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9956817,0.00010343865,0.00069362216,0.0010943124,0.0021436538,0.00028328513],"domain_scores_gemma":[0.996697,0.00039743373,0.00038426116,0.0017944471,0.00056169415,0.00016513547],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.005818332,0.0001194629,0.00016286407,0.00031354,0.0006969533,0.0011231692,0.00824764,0.000034200668,0.0000304322],"category_scores_gemma":[0.0032578814,0.00010071312,0.00000929659,0.00027491827,0.0005024687,0.008080422,0.007384073,0.00013676481,0.0000025848833],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022119601,0.00014776134,0.01322474,0.00003955949,0.00007452416,0.00008227353,0.012487652,0.000052165295,0.00005646049,0.03213261,0.01686907,0.924612],"study_design_scores_gemma":[0.0015976826,0.00018883358,0.3254832,0.00032130285,0.000047486556,0.00058486516,0.052431036,0.15859367,0.000013387966,0.013523433,0.44654644,0.000668688],"about_ca_topic_score_codex":0.057222184,"about_ca_topic_score_gemma":0.658116,"teacher_disagreement_score":0.9239433,"about_ca_system_score_codex":0.00016790372,"about_ca_system_score_gemma":0.0009895929,"threshold_uncertainty_score":0.99991375},"labels":[],"label_agreement":null},{"id":"W2889745882","doi":"10.23889/ijpds.v3i4.671","title":"SAGE: supporting secondary data analysis and expediting knowledge mobilization with linked administrative, service delivery, and research data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Data sharing; Data governance; Transparency (behavior); Data security; Knowledge management; Public relations; Business; Service (business); Computer science; Data quality; Computer security; Political science; Marketing","score_opus":0.7267985662747994,"score_gpt":0.6799186325727252,"score_spread":0.04687993370207422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889745882","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93961763,0.00022691417,0.048189957,0.007566146,0.0005938579,0.0006550791,0.0025198404,0.000031571693,0.00059900736],"genre_scores_gemma":[0.95624304,0.00027058204,0.03675165,0.00018813006,0.00097251806,0.000004012199,0.0053719,0.000013561355,0.00018460599],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955114,0.00013459857,0.00067961443,0.0011283638,0.00219525,0.00035078748],"domain_scores_gemma":[0.98554903,0.0042442223,0.0004830315,0.0024063766,0.0068623186,0.00045503912],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0219303,0.00011456144,0.00021016329,0.0007418475,0.00091551524,0.0008095238,0.0033979376,0.00010033366,0.00010610748],"category_scores_gemma":[0.025972016,0.00009306944,0.000014150471,0.0014443983,0.00098755,0.004208129,0.0048184944,0.0009734246,0.0000040086384],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016234329,0.00048035252,0.7524367,0.00034369717,0.0010743815,0.00009463865,0.0022934405,0.000026383123,0.0059131063,0.004259044,0.002304172,0.22915064],"study_design_scores_gemma":[0.0018313533,0.00061220175,0.3315005,0.0006011238,0.00031559737,0.00037265432,0.0023154202,0.6535964,0.0003042859,0.0034319519,0.004866867,0.0002516488],"about_ca_topic_score_codex":0.00037736408,"about_ca_topic_score_gemma":0.0065000146,"teacher_disagreement_score":0.65357,"about_ca_system_score_codex":0.000100678044,"about_ca_system_score_gemma":0.0016885981,"threshold_uncertainty_score":0.98223263},"labels":[],"label_agreement":null},{"id":"W2889758150","doi":"10.23889/ijpds.v3i4.828","title":"A Population-Based Examination of Benzodiazepine Receptor Agonist &amp; Z-drug Dispensations in the Alberta Population: Prevalence of Use and Indicators of Potentially Inappropriate Use and Prescribing","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; College of Physicians and Surgeons of Ontario; McGill University","funders":"","keywords":"Medicine; Population; Adverse effect; Benzodiazepine; Pharmacoepidemiology; Emergency medicine; Family medicine; Medical prescription; Pediatrics; Internal medicine; Environmental health; Pharmacology","score_opus":0.16636403557767834,"score_gpt":0.4164480557875103,"score_spread":0.250084020209832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889758150","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99623984,0.000027841117,0.0018258006,0.00079664204,0.00032262897,0.0004818362,0.0002909366,0.0000033641738,0.000011133454],"genre_scores_gemma":[0.9893929,0.000056060886,0.009760531,0.00008767096,0.00007502428,0.000004302278,0.00058298244,0.000006839888,0.000033730805],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99790376,0.00012884663,0.0007389982,0.00026025527,0.000843619,0.00012454638],"domain_scores_gemma":[0.99737185,0.0007626496,0.00087457924,0.00030108442,0.0006131144,0.0000767062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017585563,0.00009958132,0.00018455477,0.00049852976,0.00016761647,0.0001351215,0.0004232283,0.000037361773,0.00003081962],"category_scores_gemma":[0.005150888,0.00007563262,0.000035752368,0.00042337048,0.00026413373,0.0028418477,0.00012517988,0.00012761213,2.7674085e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021435726,0.0001255952,0.9929802,0.000090502435,0.000020709913,2.896449e-7,0.000422123,0.00011396181,0.0014205797,0.0016893371,0.000015636919,0.002906701],"study_design_scores_gemma":[0.00080901315,0.00009072833,0.9811649,0.00025376555,0.00007824552,0.00001428342,0.000042635274,0.01680552,0.0002805977,0.00015661566,0.00023420328,0.00006949338],"about_ca_topic_score_codex":0.0025190513,"about_ca_topic_score_gemma":0.000757863,"teacher_disagreement_score":0.016691558,"about_ca_system_score_codex":0.00005582448,"about_ca_system_score_gemma":0.00008367581,"threshold_uncertainty_score":0.6166466},"labels":[],"label_agreement":null},{"id":"W2889797006","doi":"10.23889/ijpds.v3i4.1021","title":"The Economic Impacts of ICD-9 to ICD-10 Health Indicator Coding System Transition in the Calgary Region","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Business; Coding (social sciences); Health care; Government (linguistics); Actuarial science; Operations management; Economics; Economic growth","score_opus":0.25555134125154944,"score_gpt":0.5191808334251005,"score_spread":0.263629492173551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889797006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79386556,0.000102947706,0.10390427,0.08524379,0.01242348,0.0027150295,0.00039618212,0.00005697754,0.0012917358],"genre_scores_gemma":[0.99585706,0.00005962337,0.0006130416,0.0024146643,0.0008821317,0.000022797713,0.00012281028,0.000005053279,0.000022812299],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99740344,0.0002568327,0.0010847975,0.00017899035,0.00072285323,0.00035307472],"domain_scores_gemma":[0.9977904,0.0005115453,0.00084249116,0.0003410355,0.00032648316,0.00018806111],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.010906438,0.00007343148,0.00013130525,0.00032433606,0.002010461,0.0000872307,0.0014578683,0.00005243999,0.000024953224],"category_scores_gemma":[0.0010115978,0.00004477613,0.000027021983,0.00023291055,0.00013115858,0.0010040306,0.0001062666,0.0003013542,0.000049267328],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002890757,0.0001605964,0.08256702,0.0011321666,0.00008530132,0.000009200086,0.07852733,0.0010808853,0.00031784014,0.38337845,0.26344594,0.1864045],"study_design_scores_gemma":[0.0028299452,0.00086159806,0.52972573,0.0033283231,0.000020339687,0.00019635542,0.016116953,0.3149407,0.0000418421,0.0021320232,0.12947491,0.00033129464],"about_ca_topic_score_codex":0.0011868397,"about_ca_topic_score_gemma":0.000996251,"teacher_disagreement_score":0.4471587,"about_ca_system_score_codex":0.0010815298,"about_ca_system_score_gemma":0.0012392813,"threshold_uncertainty_score":0.9992888},"labels":[],"label_agreement":null},{"id":"W2889799971","doi":"10.23889/ijpds.v3i4.925","title":"Cancer Screening in the Toronto Central LHIN by Sub-region and Neighbourhood: Evidence from an Applied Health Research Question (AHRQ)","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Medicine; Family medicine; Immigration; Cancer screening; Psychological intervention; Cervical cancer; Health care; Population; Cancer; Cervical cancer screening; Neighbourhood (mathematics); Demography; Gerontology; Environmental health; Nursing; Geography; Internal medicine; Political science","score_opus":0.3894744167739918,"score_gpt":0.554729586927895,"score_spread":0.16525517015390317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889799971","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95090497,0.00174214,0.030497396,0.015182194,0.00088474655,0.0005269804,0.00015743154,0.000016331709,0.00008784238],"genre_scores_gemma":[0.993013,0.0007679037,0.0032749863,0.0014954146,0.0011853421,0.00001288907,0.0002315123,0.0000066402386,0.000012262567],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997108,0.00013045986,0.00036699555,0.0004365884,0.0015752167,0.00038278577],"domain_scores_gemma":[0.9985272,0.00016020698,0.00020176715,0.000326049,0.0005685846,0.00021616371],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044339104,0.000091985385,0.00012491242,0.000127583,0.00057884963,0.00043922188,0.0010715598,0.00003886596,0.000042790874],"category_scores_gemma":[0.00077188265,0.00006889925,0.00001753407,0.00027315618,0.0002515874,0.0033263173,0.00015925893,0.0002557589,0.0000010171751],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012669996,0.00009055206,0.5690173,0.000010537574,0.000026773465,0.000013182861,0.0027198046,0.00014299687,0.00569233,0.002984619,0.010311142,0.40772378],"study_design_scores_gemma":[0.00063491584,0.0002838019,0.9618737,0.00067605154,0.000009987641,0.00009724596,0.0010291238,0.031984154,0.00024263455,0.0009458994,0.0021237358,0.00009872362],"about_ca_topic_score_codex":0.054990303,"about_ca_topic_score_gemma":0.023576489,"teacher_disagreement_score":0.40762508,"about_ca_system_score_codex":0.00057468744,"about_ca_system_score_gemma":0.00037282528,"threshold_uncertainty_score":0.9942407},"labels":[],"label_agreement":null},{"id":"W2889810020","doi":"10.23889/ijpds.v3i4.633","title":"Mortality among single fathers as compared with single mothers and partnered fathers: a cohort study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Intergenerational Family Dynamics and Caregiving","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; Women's College Hospital; Centre for Addiction and Mental Health; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Hazard ratio; Demography; Single mothers; Medicine; Proportional hazards model; Cohort; Population; Single parent; Cohort study; Environmental health; Psychology; Developmental psychology; Confidence interval","score_opus":0.07961503279551196,"score_gpt":0.3970584744943685,"score_spread":0.3174434416988565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889810020","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9909831,0.0000075866883,0.004576838,0.00030024012,0.0012999319,0.00044195759,0.00006572652,0.000026609621,0.0022979758],"genre_scores_gemma":[0.9977318,0.0000053112162,0.0011285767,0.00014028262,0.0005908559,0.0000114198,0.0000722339,0.000011774967,0.0003077264],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974768,0.000090123904,0.00031681044,0.00043670266,0.0014118536,0.00026767218],"domain_scores_gemma":[0.99819106,0.000068886504,0.0002939228,0.0002730723,0.0010083555,0.0001646967],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0021604155,0.00011730359,0.00013113293,0.00017929042,0.0012344198,0.0011084528,0.0011494255,0.000034704357,0.000067861605],"category_scores_gemma":[0.0005100722,0.00010113412,0.000030334655,0.0002707756,0.00082771323,0.0022154867,0.00015576239,0.000088963985,0.000003493382],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006340215,0.00021307438,0.98475796,0.0000010347804,0.00011013874,0.000005175919,0.0051329196,0.00030035817,0.0008791039,0.006985507,0.00023883714,0.0013124698],"study_design_scores_gemma":[0.00088936806,0.00051659945,0.93908834,0.0000742867,0.00006408022,0.000023218567,0.016237987,0.03600772,0.00006889021,0.002481817,0.0041902433,0.0003574411],"about_ca_topic_score_codex":0.0041304952,"about_ca_topic_score_gemma":0.017506143,"teacher_disagreement_score":0.04566963,"about_ca_system_score_codex":0.0003238613,"about_ca_system_score_gemma":0.00020706719,"threshold_uncertainty_score":0.9999285},"labels":[],"label_agreement":null},{"id":"W2889817414","doi":"10.23889/ijpds.v3i4.1039","title":"Survival outcomes of a population-based cohort of adolescent and young adult (AYA), acute lymphoblastic leukemia (ALL) patients in Ontario, Canada: The IMPACT Cohort","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Childhood Cancer Survivors' Quality of Life","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hospital for Sick Children; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Cohort; Population; Young adult; Cohort study; Pediatrics; Cancer; Malignancy; Internal medicine; Oncology; Environmental health","score_opus":0.02981574770214843,"score_gpt":0.35042811114641786,"score_spread":0.3206123634442694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889817414","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996334,0.000006617007,0.00046323173,0.00055539294,0.0016080902,0.00046330583,0.0005375066,0.00000470194,0.000027127197],"genre_scores_gemma":[0.99827886,0.0000071856343,0.00050164387,0.00033131044,0.000102587604,0.000004485943,0.0007431939,0.000010012468,0.000020735753],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99672407,0.000052255655,0.0008774213,0.000318088,0.0018083442,0.00021981345],"domain_scores_gemma":[0.99730486,0.00017299652,0.0006760137,0.00041285553,0.0012890658,0.00014423138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013521727,0.0001467307,0.00034834113,0.00025246752,0.00013237768,0.000056183544,0.0007601965,0.000037942435,0.000037841517],"category_scores_gemma":[0.0014586131,0.00010444904,0.00006453057,0.00022462472,0.0002021543,0.0005644286,0.00015311544,0.00015918358,2.922585e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028167263,0.00008262425,0.9984197,0.000009789245,0.00014405794,0.0000017013278,0.00013500803,0.00024410654,0.000035254474,0.00008973818,0.00029951366,0.00025685053],"study_design_scores_gemma":[0.0016782527,0.00012157931,0.986904,0.00018127779,0.00008258641,0.00002012958,0.000041992582,0.010731405,0.000044028173,0.00006921316,0.000028139306,0.00009739457],"about_ca_topic_score_codex":0.9611968,"about_ca_topic_score_gemma":0.96118116,"teacher_disagreement_score":0.011515682,"about_ca_system_score_codex":0.0023059289,"about_ca_system_score_gemma":0.0026460392,"threshold_uncertainty_score":0.60299236},"labels":[],"label_agreement":null},{"id":"W2889821468","doi":"10.23889/ijpds.v3i4.848","title":"Linkage of Chronic Disease Data from Provincial Sources for Strategic Decision Support and Population Health Surveillance in British Columbia (BC)","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Stantec (Canada); Provincial Health Services Authority; BC Centre for Disease Control","funders":"","keywords":"Agency (philosophy); Business; Health care; Population; Disease; Medicine; Data governance; Environmental health; Data quality; Economic growth; Service (business); Economics","score_opus":0.1357579806471127,"score_gpt":0.487952524262457,"score_spread":0.3521945436153443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889821468","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97691816,0.00025557028,0.00515289,0.0020632476,0.003159669,0.0010598822,0.011347174,0.000019170113,0.000024219222],"genre_scores_gemma":[0.982416,0.00022819107,0.005527849,0.00111839,0.0015761008,0.0000181452,0.00901336,0.000014050111,0.00008791744],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970563,0.00012187173,0.0011130364,0.00057420676,0.0007410676,0.00039349095],"domain_scores_gemma":[0.99712074,0.0005524648,0.0008718315,0.0005721853,0.0006430603,0.00023971277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037993242,0.00009013399,0.0002687903,0.00017941148,0.0010284825,0.0002575129,0.0016417715,0.000068811605,0.00014914665],"category_scores_gemma":[0.0014313093,0.00011238594,0.000027951914,0.00020626499,0.00014327899,0.002099515,0.00063423463,0.00021053827,0.0000033904678],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001592469,0.000049575345,0.95471936,0.000077160956,0.000008745007,0.0000020134353,0.00008557978,0.00001429066,0.000017933673,0.00018453946,0.009147675,0.03553387],"study_design_scores_gemma":[0.0012924423,0.00014532043,0.9597532,0.00024640767,0.0000070865526,0.0000043734904,0.00010659992,0.023204952,3.2885512e-7,0.006969357,0.008162367,0.0001075606],"about_ca_topic_score_codex":0.092668824,"about_ca_topic_score_gemma":0.59302866,"teacher_disagreement_score":0.50035983,"about_ca_system_score_codex":0.0006850733,"about_ca_system_score_gemma":0.0037742672,"threshold_uncertainty_score":0.9133732},"labels":[],"label_agreement":null},{"id":"W2889831492","doi":"10.23889/ijpds.v3i4.849","title":"Evaluating the Manitoba Infant Feeding Database: Linking an infant feeding data repository with total population administrative data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Breastfeeding Practices and Influences","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Winnipeg Regional Health Authority; Manitoba Health; University of Manitoba; Public Health Agency of Canada","funders":"","keywords":"Breastfeeding; Data collection; Medicine; Data quality; Population; Medical record; Database; Infant mortality; Infant formula; Pediatrics; Breast feeding; Family medicine; Demography; Environmental health; Computer science; Statistics; Business; Mathematics","score_opus":0.278993550810474,"score_gpt":0.499386826417888,"score_spread":0.220393275607414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889831492","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.984133,0.00006737147,0.005442918,0.004403027,0.0038998944,0.00055901596,0.0012040443,0.000056864108,0.00023386278],"genre_scores_gemma":[0.94505244,0.000016223574,0.04203898,0.000275506,0.0045436244,0.0000058541755,0.008005332,0.00002125701,0.000040780353],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99527186,0.000087497225,0.0008164212,0.0010847716,0.002363706,0.00037577204],"domain_scores_gemma":[0.9946347,0.00030672704,0.0011623608,0.0022868337,0.0013825556,0.00022685375],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0071697724,0.00021847674,0.00021980966,0.00028924458,0.0018508335,0.0017689833,0.0047614574,0.000060024806,0.000029919425],"category_scores_gemma":[0.003159161,0.0001456686,0.000026017993,0.00046822522,0.00040460873,0.019130748,0.0021331448,0.00047234845,0.00000399337],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030711188,0.00034546177,0.8230271,0.00007171355,0.00051298237,0.00008190723,0.0014807967,0.0006906523,0.038317636,0.0031963908,0.002061506,0.12714279],"study_design_scores_gemma":[0.0007963113,0.00068894797,0.53471863,0.0006455796,0.00020238041,0.0037333716,0.0009517553,0.45614538,0.00016855921,0.00010416281,0.0016174031,0.00022752315],"about_ca_topic_score_codex":0.0029604046,"about_ca_topic_score_gemma":0.0007961896,"teacher_disagreement_score":0.45545474,"about_ca_system_score_codex":0.00020904215,"about_ca_system_score_gemma":0.0005969561,"threshold_uncertainty_score":0.9994486},"labels":[],"label_agreement":null},{"id":"W2889833658","doi":"10.23889/ijpds.v3i4.673","title":"Education and social service use patterns of children and youth with neurodevelopmental disorders","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare innovation and challenges","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; Government of Alberta","funders":"","keywords":"Government (linguistics); Autism spectrum disorder; Fetal Alcohol Spectrum Disorder; Medicine; Intervention (counseling); Service (business); Cerebral palsy; Psychology; Neurodevelopmental disorder; Autism; Psychiatry; Clinical psychology; Family medicine; Pregnancy; Business","score_opus":0.09468927655348064,"score_gpt":0.41356661250740734,"score_spread":0.3188773359539267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889833658","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98809254,0.000007587609,0.00064564525,0.010290614,0.0005645725,0.000122321,0.00021565903,0.00000810257,0.000052956464],"genre_scores_gemma":[0.99759114,0.00007484029,0.0012891123,0.00050528516,0.00031141602,0.0000011487498,0.00019916642,0.0000038713256,0.000024025017],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989831,0.00003035531,0.00018537088,0.00018387433,0.00050448434,0.000112844384],"domain_scores_gemma":[0.99890673,0.00002574703,0.00018728596,0.00007082403,0.00074977643,0.000059631748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006488645,0.000049768973,0.00005322576,0.00015800208,0.0006614336,0.00023416814,0.00041263486,0.000024009385,0.00001018128],"category_scores_gemma":[0.00014157903,0.000044302386,0.000005606766,0.00017783958,0.00023830002,0.001847555,0.000097569085,0.000055838445,3.263886e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051674866,0.00006972742,0.8111016,0.0000062419713,0.000017675558,7.654595e-8,0.018712845,5.4300483e-7,0.00004090484,0.04028719,0.00011041794,0.12960109],"study_design_scores_gemma":[0.0002221471,0.000034594334,0.99099964,0.000028301383,0.000005099063,0.000009111737,0.005698232,0.00009026785,0.0000080890495,0.00038338779,0.0024505763,0.00007056741],"about_ca_topic_score_codex":0.002691333,"about_ca_topic_score_gemma":0.009440799,"teacher_disagreement_score":0.17989802,"about_ca_system_score_codex":0.000046169487,"about_ca_system_score_gemma":0.00035622285,"threshold_uncertainty_score":0.52681875},"labels":[],"label_agreement":null},{"id":"W2889835285","doi":"10.23889/ijpds.v3i4.881","title":"Training Coding Specialists for the Future: Methods and Materials for the Beta Version of ICD-11","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information; Toronto Metropolitan University; University of Calgary","funders":"","keywords":"Coding (social sciences); Computer science; Terminology; Psychology; Statistics","score_opus":0.5100154336825988,"score_gpt":0.6112938685375764,"score_spread":0.10127843485497756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889835285","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025148049,0.00009408501,0.9268463,0.022931717,0.022436354,0.001407945,0.0010208569,0.000014643235,0.00010001002],"genre_scores_gemma":[0.89483577,0.00024351254,0.091427125,0.0020342811,0.010913651,0.00008006669,0.00031173587,0.000012278213,0.00014157048],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983139,0.00009333387,0.0006568457,0.00015103338,0.00055172597,0.0002331722],"domain_scores_gemma":[0.9953708,0.0024666607,0.00068441505,0.00021832492,0.0011809529,0.00007882965],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.014752488,0.00006546,0.00012297962,0.00011210922,0.0028054146,0.000095902615,0.00096402987,0.000054731645,0.00007726669],"category_scores_gemma":[0.004123236,0.000036880923,0.000029441377,0.000113616865,0.00020408284,0.0008291566,0.00017527331,0.000119447686,0.0000015138925],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012544388,0.00002886745,0.003142649,0.0003522834,0.00009230149,1.617733e-7,0.011168727,0.00004921517,0.0048239394,0.30735353,0.066966176,0.6047677],"study_design_scores_gemma":[0.0016658432,0.00015366431,0.03987692,0.00032530655,0.00006598653,0.000014935909,0.004424145,0.104551695,0.0006873532,0.0072060446,0.8409056,0.00012248494],"about_ca_topic_score_codex":0.00008045767,"about_ca_topic_score_gemma":0.00011541831,"teacher_disagreement_score":0.86968774,"about_ca_system_score_codex":0.000107440734,"about_ca_system_score_gemma":0.0003233453,"threshold_uncertainty_score":0.9984928},"labels":[],"label_agreement":null},{"id":"W2889867277","doi":"10.23889/ijpds.v3i4.952","title":"Measuring equity in per capita primary care investment in Ontario: Challenges for data linkage and analysis","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Capitation; Payment; Equity (law); Incentive; Business; Proxy (statistics); Actuarial science; Per capita; Primary care; Family medicine; Medicine; Finance; Economics; Environmental health","score_opus":0.44999556265736085,"score_gpt":0.5362889808120167,"score_spread":0.08629341815465585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889867277","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9655412,0.0020865898,0.0063229497,0.011796553,0.005732565,0.0018678477,0.0020215,0.00003360872,0.0045972224],"genre_scores_gemma":[0.97172093,0.00047803074,0.019007608,0.0042615016,0.0005777426,0.00004908361,0.0037139868,0.000013226964,0.00017787723],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99757516,0.000090250905,0.0007129572,0.0005519275,0.0006732162,0.0003964885],"domain_scores_gemma":[0.9979982,0.0002837273,0.00032060893,0.00065739854,0.00059956947,0.00014048872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041638147,0.00010925032,0.00024710392,0.00078380096,0.0006102806,0.00008354969,0.0019553239,0.000075219374,0.00006917655],"category_scores_gemma":[0.0005289215,0.00009761944,0.000030736777,0.0001889295,0.000100858466,0.0022404653,0.0017653971,0.00034454573,0.0000052221476],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013624491,0.000044138164,0.96861297,0.00012764381,0.00005855028,0.000003164148,0.0050527505,0.00002202966,0.00006770779,0.002707102,0.0007263444,0.022441361],"study_design_scores_gemma":[0.0009081464,0.000045430123,0.9722792,0.00010329259,0.000039785857,0.000002714106,0.00072855555,0.003756719,0.0000018941852,0.0020566862,0.019966885,0.00011068368],"about_ca_topic_score_codex":0.02583761,"about_ca_topic_score_gemma":0.62712216,"teacher_disagreement_score":0.60128456,"about_ca_system_score_codex":0.0026921027,"about_ca_system_score_gemma":0.0021767688,"threshold_uncertainty_score":0.9806494},"labels":[],"label_agreement":null},{"id":"W2889869750","doi":"10.23889/ijpds.v3i4.959","title":"Public views and recommendations on the use of linked data for research: preliminary results from a public deliberation engagement","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; University of British Columbia","funders":"","keywords":"Deliberation; Public relations; Public engagement; Harm; Data sharing; Political science; Secrecy; Internet privacy; Sociology; Psychology; Social psychology; Computer science; Medicine; Law","score_opus":0.9500920201003664,"score_gpt":0.617412246931546,"score_spread":0.33267977316882047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889869750","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06128535,0.000050360803,0.5110234,0.37223488,0.0060440125,0.002462499,0.046494935,0.000034251287,0.00037031723],"genre_scores_gemma":[0.9103077,0.0001381592,0.07337853,0.0017686631,0.00091798045,0.000043895347,0.012922271,0.000011750503,0.00051106303],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9940707,0.0006748513,0.0012439656,0.00087494997,0.0028534436,0.0002820963],"domain_scores_gemma":[0.9828424,0.009170649,0.0009462187,0.0027514114,0.004129331,0.00015998066],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.046921905,0.000103185484,0.0001415409,0.000777735,0.0016207651,0.0040068887,0.007312706,0.000037481695,0.00010345839],"category_scores_gemma":[0.10674263,0.000067816276,0.000034794626,0.000795406,0.00053361506,0.010102543,0.0033162988,0.00020754845,0.000018586901],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050547125,0.00018370568,0.00025023063,0.0000020243099,0.00005221155,4.5411716e-7,0.00047023993,0.000041231426,0.00014952125,0.11440784,0.52045095,0.36348614],"study_design_scores_gemma":[0.00052458595,0.00023578898,0.007232054,0.000041132556,0.000009620609,0.0000028394275,0.00047227505,0.15677999,0.00002540947,0.03472262,0.7998736,0.00008007495],"about_ca_topic_score_codex":0.00017989328,"about_ca_topic_score_gemma":0.00074408174,"teacher_disagreement_score":0.8490223,"about_ca_system_score_codex":0.000096399555,"about_ca_system_score_gemma":0.0002433888,"threshold_uncertainty_score":0.99967897},"labels":[],"label_agreement":null},{"id":"W2889888295","doi":"10.23889/ijpds.v3i4.759","title":"Policy advocacy to enable administrative data linking: building a civil society coalition","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Civil society; Public relations; Government (linguistics); Beneficiary; Policy advocacy; Public administration; Legislature; Business; Politics; Service delivery framework; License; Service provider; Political science; Service (business); Marketing","score_opus":0.5364738345692184,"score_gpt":0.6357405057252014,"score_spread":0.09926667115598298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889888295","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15109167,0.000021077742,0.7954987,0.036930844,0.009446911,0.0008357416,0.002065374,0.00007309924,0.004036565],"genre_scores_gemma":[0.9282518,0.000017457158,0.06500138,0.0023363833,0.002988858,0.000008062754,0.00070011435,0.000009393754,0.00068652246],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9933272,0.000092876726,0.00096026814,0.0009034624,0.004340263,0.00037590406],"domain_scores_gemma":[0.993534,0.00047731504,0.0006729246,0.0014980793,0.0035208226,0.00029680764],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.014798786,0.00014813872,0.00017118602,0.00066662475,0.0012087547,0.0025187652,0.008240783,0.000049851646,0.00043977695],"category_scores_gemma":[0.00951501,0.000118607684,0.00006735867,0.0015106425,0.00026002206,0.008601453,0.00188665,0.00017223589,0.00012777298],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068307074,0.00059227395,0.08777229,0.000016467036,0.00024965868,0.000010177198,0.0084442,0.0050243908,0.01663494,0.17679363,0.31980133,0.38397756],"study_design_scores_gemma":[0.000885112,0.0002894519,0.034097746,0.00011265976,0.000018585384,0.00011193952,0.0013328157,0.5095879,0.0008589176,0.0643171,0.3880509,0.0003368699],"about_ca_topic_score_codex":0.00017852076,"about_ca_topic_score_gemma":0.00035545806,"teacher_disagreement_score":0.77716017,"about_ca_system_score_codex":0.00034654277,"about_ca_system_score_gemma":0.002345976,"threshold_uncertainty_score":0.9988283},"labels":[],"label_agreement":null},{"id":"W2889889928","doi":"10.23889/ijpds.v3i4.704","title":"Breast cancer care in Alberta: a Patients perspective","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; University of Alberta; Alberta Health Services","funders":"","keywords":"Medicine; Breast cancer; Referral; Family medicine; Health care; Breast surgery; Cancer; Internal medicine","score_opus":0.1915335090914785,"score_gpt":0.5665343481342299,"score_spread":0.3750008390427514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889889928","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9767452,0.000023843062,0.0011851238,0.016231831,0.004203562,0.00047890385,0.0007255127,0.000011071002,0.00039498266],"genre_scores_gemma":[0.9947096,0.000022074553,0.0028347794,0.0008060272,0.0011324974,0.0000071275995,0.00042482407,0.000007913703,0.00005511762],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981645,0.000020499665,0.0005342058,0.00032186953,0.0007925449,0.00016643212],"domain_scores_gemma":[0.99564505,0.00014811446,0.00029329362,0.00023164484,0.0035766312,0.00010525133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007079252,0.00007268696,0.00009933298,0.0002924019,0.00016152348,0.00012238084,0.00057921826,0.000026454158,0.00017409983],"category_scores_gemma":[0.0036505314,0.00006288953,0.000031977197,0.0002929364,0.00012660207,0.0022188877,0.00018699765,0.00013420472,0.000014060743],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008042077,0.00014636976,0.9294162,0.0000041820877,0.000028243949,0.0000030049214,0.0007296994,0.000030266681,0.00010484097,0.001197273,0.0017357642,0.06579995],"study_design_scores_gemma":[0.0024120926,0.00015187927,0.98418546,0.00008775076,0.00003023327,0.000112226546,0.00093270635,0.0067337495,0.00002870564,0.0006352678,0.004603601,0.00008630744],"about_ca_topic_score_codex":0.007599837,"about_ca_topic_score_gemma":0.008854385,"teacher_disagreement_score":0.065713644,"about_ca_system_score_codex":0.00086497545,"about_ca_system_score_gemma":0.00045432601,"threshold_uncertainty_score":0.99900866},"labels":[],"label_agreement":null},{"id":"W2889892186","doi":"10.23889/ijpds.v3i4.676","title":"Utilizing population-based clinical and administrative data to estimate the incremental healthcare costs of dementia and frailty among community-residing care recipients.","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; University of Toronto; University of Waterloo; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Dementia; Medicine; Cohort; Gerontology; Health care; Population; Cohort study; Environmental health; Disease; Internal medicine","score_opus":0.7220297929007721,"score_gpt":0.6175660292780079,"score_spread":0.10446376362276422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889892186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9827653,0.00019678686,0.005414557,0.0068033338,0.001334075,0.00051226816,0.002912716,0.000009080554,0.00005189237],"genre_scores_gemma":[0.98321176,0.000018150611,0.013929665,0.001534183,0.00026298847,0.00000775854,0.0010220467,0.000009429673,0.0000040087493],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9965085,0.0003357492,0.002215591,0.0004529799,0.000285393,0.00020180641],"domain_scores_gemma":[0.9958367,0.0010699392,0.0017072867,0.0007575877,0.00043745968,0.00019105361],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.020862473,0.000107681444,0.0002985968,0.0002771817,0.0011786312,0.00033423124,0.0016950743,0.00004919874,0.000019157722],"category_scores_gemma":[0.010327116,0.00010738769,0.000025299649,0.00017411189,0.00034831284,0.002012497,0.0007225751,0.00021097827,0.000004975327],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034578512,0.000022924329,0.98772246,0.000021507467,0.000032753065,1.3817458e-7,0.00068041304,0.000041460033,0.0000043353875,0.009292038,0.0005029515,0.0016444677],"study_design_scores_gemma":[0.00046797073,0.00012268,0.9473133,0.00018436644,0.000010284215,0.000005523655,0.0017475078,0.047850683,0.0000069293974,0.0013160605,0.00086466194,0.000110034554],"about_ca_topic_score_codex":0.0058895177,"about_ca_topic_score_gemma":0.006836498,"teacher_disagreement_score":0.047809225,"about_ca_system_score_codex":0.00026128115,"about_ca_system_score_gemma":0.00019310476,"threshold_uncertainty_score":0.9980093},"labels":[],"label_agreement":null},{"id":"W2889892782","doi":"10.23889/ijpds.v3i4.594","title":"Principles and operational model for governing Diabetes Action Canada's data repository for patient-oriented research","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Accountability; Information governance; Transparency (behavior); Impartiality; Corporate governance; Medicine; Public relations; Nursing; Political science; Business; Information system","score_opus":0.7273494648070089,"score_gpt":0.6323983942951187,"score_spread":0.09495107051189022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889892782","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8039193,0.00009264992,0.16656405,0.015520574,0.004791948,0.0019524187,0.0068700234,0.000025595247,0.00026343286],"genre_scores_gemma":[0.9282584,0.000039390616,0.0658361,0.00038635478,0.0014717344,0.000045878445,0.0027951596,0.00001625746,0.0011507089],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9957927,0.00004113264,0.0005786191,0.0006468751,0.0025956589,0.0003450128],"domain_scores_gemma":[0.9888656,0.0030810186,0.0002636304,0.00074657757,0.006792301,0.000250869],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.008830187,0.000085593885,0.00012625832,0.00021212178,0.0013291774,0.00036872656,0.0014569613,0.00008026901,0.000006966361],"category_scores_gemma":[0.046609096,0.00007488319,0.000024628069,0.00017479193,0.00045394123,0.0016213469,0.0010004553,0.00044416895,5.3357815e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0073417253,0.0010015286,0.42239684,0.0007443565,0.0007609816,0.000018193043,0.0012151371,0.0052696536,0.06997919,0.27014554,0.11457967,0.10654717],"study_design_scores_gemma":[0.0007620126,0.0002612977,0.0119042555,0.00014703222,0.000015882062,0.000024605097,0.000106689935,0.9492433,0.000828891,0.0028480412,0.033776205,0.00008180281],"about_ca_topic_score_codex":0.0051292786,"about_ca_topic_score_gemma":0.049153958,"teacher_disagreement_score":0.94397366,"about_ca_system_score_codex":0.00054170773,"about_ca_system_score_gemma":0.0035981268,"threshold_uncertainty_score":0.999971},"labels":[],"label_agreement":null},{"id":"W2889896578","doi":"10.23889/ijpds.v3i4.887","title":"Linking Antimicrobial Resistance Surveillance Data to Provincial Hospital Records: A Descriptive Study of Patient and Facility-level Characteristics","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Medicine; Cohort; Methicillin-resistant Staphylococcus aureus; Health care; Emergency medicine; Descriptive statistics; Infection control; Psychological intervention; Public hospital; Comorbidity; Public health; Population; Antibiotic resistance; Medical emergency; Family medicine; Environmental health; Intensive care medicine; Internal medicine; Staphylococcus aureus; Nursing; Antibiotics","score_opus":0.06239423975672117,"score_gpt":0.3259799388136979,"score_spread":0.26358569905697676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889896578","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9857463,0.000036947215,0.0041951975,0.00026927333,0.0039624614,0.00039111622,0.0053768526,0.000009845854,0.000011957203],"genre_scores_gemma":[0.99637675,0.000018905037,0.0025015222,0.00005679763,0.00018671958,0.0000013403208,0.00074869127,0.0000053294693,0.000103945255],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998473,0.000064114065,0.0005161219,0.0005273079,0.00020512365,0.00021432085],"domain_scores_gemma":[0.99807155,0.00006739766,0.0004291652,0.0005471187,0.0008455939,0.000039176422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009812405,0.00011228015,0.00018603654,0.00016787459,0.00045795142,0.00012260908,0.0017191006,0.000050239258,0.000011952037],"category_scores_gemma":[0.0011176914,0.000097261895,0.000016118605,0.00017351647,0.00033462988,0.00092367106,0.00095089246,0.00013402922,0.000007818179],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029162907,0.0015691948,0.8383149,0.00006226897,0.00034477195,0.000020054596,0.010699188,0.000006407806,0.0797071,0.00048610123,0.009485877,0.056387864],"study_design_scores_gemma":[0.0018052597,0.0012003193,0.97360194,0.00034743955,0.0000395192,0.00006496631,0.0019142864,0.0002755298,0.0023014033,0.00011278773,0.0179401,0.00039646254],"about_ca_topic_score_codex":0.0002486733,"about_ca_topic_score_gemma":0.0019980217,"teacher_disagreement_score":0.13528705,"about_ca_system_score_codex":0.00007319613,"about_ca_system_score_gemma":0.00016656441,"threshold_uncertainty_score":0.39662248},"labels":[],"label_agreement":null},{"id":"W2889909038","doi":"10.23889/ijpds.v3i4.757","title":"Exploring Alternative Designs using ‘Big’ Administrative Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Programmer; Computer science; Missing data; Population; Set (abstract data type); Covariate; Macro; Sample (material); Data science; Medicine; Environmental health; Machine learning","score_opus":0.9893349254163367,"score_gpt":0.7973638719700463,"score_spread":0.1919710534462904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889909038","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57431895,0.000008551235,0.3836476,0.0074348724,0.027420495,0.001334585,0.004671255,0.00008077266,0.0010829398],"genre_scores_gemma":[0.93570817,0.000032814194,0.0546994,0.003012725,0.0059598535,0.000034143603,0.00039367974,0.000019826055,0.00013939594],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952034,0.00033592695,0.0011831489,0.0007890262,0.0017534948,0.0007350278],"domain_scores_gemma":[0.9936288,0.0011707577,0.0011118703,0.001187453,0.0024971098,0.00040399595],"candidate_categories":["metaresearch","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.009044975,0.00015882787,0.0001800097,0.00057651603,0.0032288441,0.00028163553,0.0061534103,0.000042503296,0.00027389545],"category_scores_gemma":[0.010909054,0.00014385812,0.00002511575,0.0007258458,0.00048712027,0.01055249,0.0018426033,0.0003707628,0.00010133188],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020211926,0.0005158213,0.36210364,0.0002089735,0.00061523577,0.000101044556,0.07667212,0.0010510861,0.038346943,0.1100405,0.08462523,0.3236982],"study_design_scores_gemma":[0.004297119,0.0005345386,0.14170042,0.0007467304,0.00007777045,0.0002466754,0.011444604,0.45601472,0.0014140131,0.010107339,0.37239158,0.001024477],"about_ca_topic_score_codex":0.0010007907,"about_ca_topic_score_gemma":0.00069335825,"teacher_disagreement_score":0.45496365,"about_ca_system_score_codex":0.00074792583,"about_ca_system_score_gemma":0.0026979516,"threshold_uncertainty_score":0.99922377},"labels":[],"label_agreement":null},{"id":"W2889915084","doi":"10.23889/ijpds.v3i4.1009","title":"Strengths and Barriers to Coding Hospital Chart Information from Health Information Manager Perspectives: A Qualitative Study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Audit; Staffing; Documentation; Coding (social sciences); Data quality; Quality management; Health care; Information quality; Quality assurance; Business; Knowledge management; Medicine; Nursing; Computer science; Information system; Accounting; Marketing; Engineering","score_opus":0.15389457340984464,"score_gpt":0.5548818709616767,"score_spread":0.4009872975518321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889915084","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8269664,0.000019030347,0.13811865,0.022334008,0.0074409354,0.002538,0.0017736079,0.00010062578,0.0007087019],"genre_scores_gemma":[0.98910856,0.000044499582,0.00514634,0.0040823105,0.00075280323,0.00004735669,0.00078720035,0.000005396627,0.000025519363],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9967831,0.00020596312,0.0011737002,0.00022761509,0.001219403,0.0003902273],"domain_scores_gemma":[0.99587965,0.0005057647,0.00092651736,0.00029536893,0.0017530901,0.0006395928],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.0059370045,0.0001299382,0.00018401121,0.0006615065,0.0026820127,0.0003403646,0.00084010634,0.00005794361,0.00020919109],"category_scores_gemma":[0.012547377,0.00011435637,0.000021061796,0.00036949269,0.00013255267,0.011745801,0.00037776786,0.00035344952,0.000133456],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002619592,0.000046857167,0.010699129,0.000044457505,0.000049560258,3.3906346e-7,0.8859624,0.000023821587,0.0000036564347,0.011302577,0.023316482,0.06828873],"study_design_scores_gemma":[0.001984338,0.0007633535,0.06786491,0.0003179021,0.000013789439,0.0000031983902,0.814651,0.03039243,0.000001639807,0.0013876006,0.082376175,0.00024366293],"about_ca_topic_score_codex":0.0015002688,"about_ca_topic_score_gemma":0.00021838772,"teacher_disagreement_score":0.16214214,"about_ca_system_score_codex":0.0006376407,"about_ca_system_score_gemma":0.000817558,"threshold_uncertainty_score":0.99861634},"labels":[],"label_agreement":null},{"id":"W2889917103","doi":"10.23889/ijpds.v3i4.737","title":"International Comparison of Approaches to Common Data Models for Comparative Effectiveness Research","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Dalhousie University","funders":"","keywords":"General partnership; Pharmacoepidemiology; Observational study; Session (web analytics); Computer science; Data sharing; Data science; Comparative effectiveness research; Medicine; Business; Alternative medicine; Finance; World Wide Web","score_opus":0.962161309747362,"score_gpt":0.6759778645161746,"score_spread":0.28618344523118744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889917103","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21816543,0.00017800344,0.7379955,0.01917971,0.0074574673,0.0022236058,0.012619414,0.000025331678,0.0021555177],"genre_scores_gemma":[0.9542975,0.0000070085002,0.042620074,0.00027751894,0.0011017607,0.000056661444,0.0015752286,0.000013583606,0.000050661656],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954986,0.00022641133,0.0024958402,0.00082303927,0.00061769545,0.00033840895],"domain_scores_gemma":[0.99397165,0.0019431663,0.0016039036,0.001045708,0.0012549296,0.00018064088],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.045626957,0.00012404688,0.00055499014,0.0009880069,0.000591387,0.00040304346,0.005357581,0.000060949584,0.000045500274],"category_scores_gemma":[0.00679649,0.00014140668,0.00005130202,0.0003774857,0.00033876236,0.0043426296,0.0010173629,0.00017058341,0.00006199006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007758681,0.0005836978,0.10443627,0.00012907154,0.00030147808,2.9415432e-7,0.0043684617,0.018081877,0.00013324524,0.8101683,0.05584467,0.0051767654],"study_design_scores_gemma":[0.0007668483,0.0001890752,0.024766145,0.00012206046,0.0000051366196,0.0000066856887,0.00074812945,0.87564445,0.000106118794,0.055819478,0.041650385,0.00017546721],"about_ca_topic_score_codex":0.000539044,"about_ca_topic_score_gemma":0.00033505395,"teacher_disagreement_score":0.8575626,"about_ca_system_score_codex":0.0006069783,"about_ca_system_score_gemma":0.00024977347,"threshold_uncertainty_score":0.9955808},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":["metaresearch"],"domain":"reproducibility","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"split"},{"id":"W2889926289","doi":"10.23889/ijpds.v3i4.954","title":"Examination of High-Cost Patients in Ontario","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Health care; Medicine; Mental health; Total cost; Environmental health; Family medicine; Business; Psychiatry; Economics; Economic growth","score_opus":0.15953080512629825,"score_gpt":0.4969919021296387,"score_spread":0.3374610970033404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889926289","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98791164,0.0000027243375,0.0016420874,0.0010408107,0.0070096166,0.00041422,0.00018892996,0.00000839444,0.0017815756],"genre_scores_gemma":[0.994557,0.000008414379,0.0028167188,0.0012240502,0.00035700906,0.000010455255,0.0005819358,0.000005522022,0.00043885037],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980132,0.0000738719,0.0006978016,0.00022412626,0.000742189,0.00024880093],"domain_scores_gemma":[0.99744296,0.00017053181,0.000509596,0.00026932018,0.0015289054,0.00007865931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002294886,0.000065803484,0.0001279524,0.00046435432,0.00043752146,0.000027116716,0.0011406252,0.000051807303,0.00034623945],"category_scores_gemma":[0.0009835032,0.000058129262,0.000019321487,0.00022766889,0.00010190603,0.001918692,0.00030199,0.00024408136,0.000023631237],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007587107,0.000054931348,0.9718572,0.000007725421,0.0000049195332,4.992884e-7,0.00070564396,0.000006708368,0.000039444338,0.0036297995,0.0035963836,0.020020884],"study_design_scores_gemma":[0.00090789987,0.000060626284,0.9734281,0.000054646076,0.0000033276356,0.0000011465811,0.000054825472,0.0003880479,0.000018115888,0.0013322341,0.023696136,0.000054897933],"about_ca_topic_score_codex":0.037552245,"about_ca_topic_score_gemma":0.21242505,"teacher_disagreement_score":0.17487282,"about_ca_system_score_codex":0.0014929934,"about_ca_system_score_gemma":0.0013654294,"threshold_uncertainty_score":0.96885675},"labels":[],"label_agreement":null},{"id":"W2889944068","doi":"10.23889/ijpds.v3i4.677","title":"Duration of maternal mental health-related outcomes after an infant’s death: A retrospective matched-cohort study using linkable administrative data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Grief, Bereavement, and Mental Health","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Medicine; Anxiety; Depression (economics); Mental health; Cohort; Medical prescription; Psychiatry; Cohort study; Pediatrics; Relative risk; Confidence interval; Internal medicine","score_opus":0.1600960354021663,"score_gpt":0.49897475009042075,"score_spread":0.3388787146882545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889944068","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9888005,0.000018513294,0.0017554172,0.0003649486,0.0053553768,0.00097167154,0.002587488,0.000019277488,0.00012680821],"genre_scores_gemma":[0.99301046,0.0000069604253,0.004863646,0.0001620903,0.0003280933,0.000015162864,0.0014276342,0.00001598597,0.0001699908],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99654454,0.0001410202,0.00112515,0.00071966666,0.0011215461,0.00034806624],"domain_scores_gemma":[0.9971649,0.00003169201,0.0011068655,0.00090304716,0.00058884884,0.00020467056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031105976,0.00017162523,0.0002809157,0.00032392234,0.0005381633,0.00022909835,0.0018477597,0.000051928837,0.00036002233],"category_scores_gemma":[0.00014174818,0.00015095968,0.000034785844,0.00024415442,0.00019934251,0.0036101178,0.00047987967,0.00017713806,0.0000132280165],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037702738,0.00047921072,0.99438345,0.0000047456674,0.00013694454,0.0000064859496,0.002490558,0.0000028812171,0.00019222351,0.0010964277,0.00016647519,0.00066353875],"study_design_scores_gemma":[0.0011820507,0.0007097757,0.99062556,0.00006258054,0.00002911167,0.00016279228,0.0016213284,0.004679615,0.000064524924,0.00064715225,0.000083176375,0.00013234309],"about_ca_topic_score_codex":0.006043315,"about_ca_topic_score_gemma":0.0022192746,"teacher_disagreement_score":0.0050272834,"about_ca_system_score_codex":0.00053211197,"about_ca_system_score_gemma":0.0003457414,"threshold_uncertainty_score":0.91357243},"labels":[],"label_agreement":null},{"id":"W2889955345","doi":"10.23889/ijpds.v3i4.611","title":"Estimating the effect of referral for nephrology care on the survival of adults with advanced chronic kidney disease in a real-world clinical setting","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; University of Calgary","funders":"","keywords":"Medicine; Hazard ratio; Proportional hazards model; Referral; Nephrology; Confounding; Kidney disease; Internal medicine; Survival analysis; Cohort; Randomized controlled trial; Confidence interval; Clinical trial; Selection bias; Marginal structural model; Emergency medicine; Family medicine; Pathology","score_opus":0.1553901981825603,"score_gpt":0.515340847866065,"score_spread":0.35995064968350476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889955345","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.933122,0.000007641648,0.063711226,0.0010213247,0.0007274828,0.0009811857,0.00034712141,0.000022021733,0.00006002408],"genre_scores_gemma":[0.9469567,0.000003951381,0.05250069,0.00007117439,0.0003241033,0.000041894167,0.00008476528,0.000011235852,0.0000054759425],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981901,0.00014058012,0.00065723166,0.00026940744,0.0005499978,0.00019268315],"domain_scores_gemma":[0.9954121,0.0025207757,0.0008340264,0.0004854971,0.00067802216,0.00006956804],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003265491,0.00011052272,0.00020091684,0.00015610487,0.00020583921,0.000039771156,0.0014268429,0.000026212263,0.000007914425],"category_scores_gemma":[0.010444571,0.000059245824,0.000053995886,0.0002361947,0.00046981277,0.00059374596,0.00019820408,0.00018835838,2.5131465e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.017142756,0.00030187596,0.50339514,0.0006079206,0.00021566215,0.000010245548,0.0025296551,0.011012125,0.003054095,0.2921275,0.001979013,0.16762401],"study_design_scores_gemma":[0.006842019,0.0076784734,0.19603553,0.00489583,0.00016864971,0.000024727906,0.00047679598,0.64622784,0.005574865,0.13072678,0.000806955,0.0005415283],"about_ca_topic_score_codex":0.000058957674,"about_ca_topic_score_gemma":0.0006087406,"teacher_disagreement_score":0.6352157,"about_ca_system_score_codex":0.00016088258,"about_ca_system_score_gemma":0.0002545311,"threshold_uncertainty_score":0.9978909},"labels":[],"label_agreement":null},{"id":"W2889964875","doi":"10.23889/ijpds.v3i4.666","title":"Using Planning Data to Monitor the Health of Communities - The Healthy Development: Monitoring and Mapping Project","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Public Health Policies and Epidemiology","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Built environment; Neighbourhood (mathematics); Urban planning; Environmental planning; Land use; Baseline (sea); Business; Scale (ratio); Environmental resource management; Health indicator; Transport engineering; Geography; Environmental health; Civil engineering; Engineering; Cartography; Population; Environmental science","score_opus":0.4690022528564238,"score_gpt":0.5061678346586314,"score_spread":0.03716558180220758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889964875","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93791735,0.0001573285,0.013775168,0.042895135,0.0045905183,0.00046124955,0.00008754952,0.000018606397,0.00009711468],"genre_scores_gemma":[0.9811852,0.000020247022,0.0102921,0.005746781,0.002647914,0.000003342111,0.00009459084,0.000005982208,0.000003858559],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.998599,0.000035715897,0.0004991233,0.00016777139,0.00040729856,0.0002911227],"domain_scores_gemma":[0.99837416,0.00016011752,0.0005320933,0.00044423502,0.00046232395,0.00002704094],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005757729,0.000074137584,0.00011404227,0.0002659023,0.0018898194,0.00046856963,0.0026598102,0.000016255924,0.000002236944],"category_scores_gemma":[0.0009495426,0.000045951838,0.000009429234,0.00037357642,0.0002013368,0.0023649496,0.0017871003,0.00011972861,0.0000013641995],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038735426,0.00010835669,0.6702738,0.00031047297,0.00016546136,0.0000016025165,0.008700866,0.00534925,0.00024992946,0.028260099,0.12245959,0.16373324],"study_design_scores_gemma":[0.00022221176,0.000027706965,0.20365408,0.00024170073,0.000005198166,0.00003388996,0.006179666,0.20935465,0.0000020410455,0.00045653337,0.5797147,0.00010757616],"about_ca_topic_score_codex":0.015778914,"about_ca_topic_score_gemma":0.00022417691,"teacher_disagreement_score":0.4666197,"about_ca_system_score_codex":0.00008815103,"about_ca_system_score_gemma":0.00020810853,"threshold_uncertainty_score":0.99940956},"labels":[],"label_agreement":null},{"id":"W2889974878","doi":"10.23889/ijpds.v3i4.1013","title":"Identifying Knowledge Gaps with Administrative Health Data: A Cohort Study of Traumatic and Non-Traumatic Spinal Cord Injury in Alberta","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; University of Alberta; Alberta Health Services","funders":"","keywords":"Medicine; Population; Spinal cord injury; Cohort; Ambulatory; Diagnosis code; Demographics; Emergency medicine; Health care; Demography; Family medicine; Environmental health; Psychiatry; Internal medicine","score_opus":0.18383366350179653,"score_gpt":0.510467518126226,"score_spread":0.3266338546244295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889974878","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961374,0.00012393681,0.0015178231,0.0005685512,0.00071616337,0.0006798565,0.00013730515,0.0000042519723,0.0001147092],"genre_scores_gemma":[0.9968298,0.00011545683,0.0025870185,0.000060198206,0.00018314044,0.0000097022985,0.00017257039,0.0000069048565,0.000035186113],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981105,0.000035698635,0.0006402817,0.00039736924,0.0006402039,0.00017595738],"domain_scores_gemma":[0.9984164,0.00006232259,0.00041189897,0.00042341612,0.0005834988,0.000102437974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015628561,0.0001121243,0.00027637134,0.00033295088,0.00031115374,0.00009669085,0.00078600895,0.000016606895,0.000012576403],"category_scores_gemma":[0.0005874454,0.00008536218,0.0000145843715,0.0003797075,0.00031096904,0.0014400966,0.00031818516,0.0001312578,0.0000013077454],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017231504,0.0009399346,0.96432126,0.00018260653,0.00026996163,0.000012774716,0.0069264583,0.0000020855084,0.00022067165,0.00039509393,0.0013479155,0.023658074],"study_design_scores_gemma":[0.0012285964,0.003806533,0.9855332,0.00090084574,0.00006226848,0.00014890489,0.004259719,0.0035470084,0.000029501258,0.00014703235,0.00023411524,0.00010231498],"about_ca_topic_score_codex":0.0016175474,"about_ca_topic_score_gemma":0.011314883,"teacher_disagreement_score":0.02355576,"about_ca_system_score_codex":0.000099575416,"about_ca_system_score_gemma":0.00038339454,"threshold_uncertainty_score":0.631397},"labels":[],"label_agreement":null},{"id":"W2889993148","doi":"10.23889/ijpds.v3i4.767","title":"Adherence to Follow-up Care Guidelines for Breast Cancer Survivors in four Canadian provinces: a CanIMPACT study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Nova Scotia Health Authority; University of Toronto; Dalhousie University; CARE Canada; Queen's University; CancerCare Manitoba; BC Cancer Agency","funders":"","keywords":"Medicine; Breast cancer; Guideline; Population; Family medicine; Cancer; Cancer registry; Cohort; Retrospective cohort study; Demography; Health care; Pediatrics; Environmental health; Internal medicine","score_opus":0.33062867445551386,"score_gpt":0.5156433346230939,"score_spread":0.18501466016758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889993148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98635584,0.00006405973,0.001431766,0.0038355917,0.004307879,0.0013310721,0.0025379502,0.000014686731,0.00012117999],"genre_scores_gemma":[0.99344164,0.000009452878,0.0039323727,0.00110154,0.0011998041,0.000057592268,0.0000984565,0.000011796925,0.00014736419],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997616,0.000017470476,0.0005165163,0.0004635814,0.0009753366,0.000411098],"domain_scores_gemma":[0.9944707,0.00003997749,0.00018002298,0.00032297766,0.0045471066,0.0004391993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013171177,0.00013355,0.00018481408,0.0005569396,0.0003591665,0.00027553178,0.0012995542,0.000035071003,0.00007322122],"category_scores_gemma":[0.0024585465,0.00011190226,0.00004843825,0.0005334375,0.00006794506,0.0013565542,0.00013546342,0.000103589526,0.0000042482047],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062108494,0.000022782191,0.9193569,0.000010387046,0.00003191592,0.000018723473,0.0011142396,0.00019440977,0.00023716656,0.00007880044,0.0037574752,0.07455614],"study_design_scores_gemma":[0.0020563293,0.0011156466,0.9728035,0.00052210985,0.00004438691,0.00023365888,0.0053053787,0.009117602,0.000040497976,0.00013209973,0.008392175,0.00023664032],"about_ca_topic_score_codex":0.6103049,"about_ca_topic_score_gemma":0.9595116,"teacher_disagreement_score":0.34920672,"about_ca_system_score_codex":0.0014508177,"about_ca_system_score_gemma":0.002677726,"threshold_uncertainty_score":0.4750171},"labels":[],"label_agreement":null},{"id":"W2889994600","doi":"10.23889/ijpds.v3i4.1014","title":"Experiences with Coding using ICD-11: “The Codes Paint a Clearer Picture”","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Health Information; Toronto Metropolitan University; University of Calgary","funders":"","keywords":"Coding (social sciences); Computer science; Comprehension; Psychology; Medicine; Statistics","score_opus":0.4397541182420329,"score_gpt":0.5624639429758395,"score_spread":0.12270982473380654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889994600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81453025,0.000011128871,0.17484564,0.004246737,0.005512063,0.00040558382,0.000058142356,0.00003651462,0.0003539307],"genre_scores_gemma":[0.9877736,0.000007797191,0.007665908,0.002494914,0.0018624476,0.000019010764,0.00006490435,0.0000067756873,0.00010462336],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99759805,0.00010850876,0.00058551034,0.00021862514,0.0011259028,0.0003634163],"domain_scores_gemma":[0.9975536,0.0003036059,0.00054703903,0.00029896025,0.001125161,0.00017165663],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00450867,0.00008828113,0.00010553345,0.00018678521,0.0037690112,0.00018810097,0.001378851,0.0000520644,0.0002873242],"category_scores_gemma":[0.0018954186,0.000050933893,0.000019606798,0.00027880678,0.0003995536,0.0018167516,0.00023765235,0.00030862624,0.0000205905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020072816,0.00021217631,0.51025254,0.0002954445,0.00017194789,0.000019296585,0.23638706,0.001717074,0.001498317,0.10318325,0.07101826,0.073237345],"study_design_scores_gemma":[0.0017055452,0.0003149705,0.06337342,0.0011268575,0.000035109028,0.00018305592,0.06841479,0.71353436,0.00011040131,0.0016579452,0.14916775,0.0003758087],"about_ca_topic_score_codex":0.00028268193,"about_ca_topic_score_gemma":0.00028803103,"teacher_disagreement_score":0.71181726,"about_ca_system_score_codex":0.0002607604,"about_ca_system_score_gemma":0.0005987191,"threshold_uncertainty_score":0.99752796},"labels":[],"label_agreement":null},{"id":"W2889998518","doi":"10.23889/ijpds.v3i4.1035","title":"Applications of Big Data Analytics within a Dynamic Simulation Modeling Platform to Inform Osteoarthritis Care in Alberta","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Leverage (statistics); Big data; Medicine; Analytics; Decision support system; Comorbidity; Computer science; Operations management; Emergency medicine; Data mining; Engineering; Internal medicine; Artificial intelligence","score_opus":0.35728819588110294,"score_gpt":0.5475778485789006,"score_spread":0.19028965269779763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889998518","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35399163,0.000025188478,0.6389397,0.0027628448,0.0018010444,0.0012085387,0.0010970699,0.000016246204,0.00015778696],"genre_scores_gemma":[0.96270657,0.000011597548,0.032241654,0.00034770335,0.00052829477,0.000010269105,0.0041134213,0.000011961146,0.000028554681],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969017,0.00001262463,0.0014347595,0.00042290747,0.0010400015,0.00018798691],"domain_scores_gemma":[0.9958654,0.00033886996,0.0005685072,0.00091022847,0.0021665653,0.00015041606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001954893,0.00010517102,0.00017988285,0.0007165022,0.0002063768,0.00013822652,0.0014457054,0.00004950323,0.000020983765],"category_scores_gemma":[0.0073257745,0.00010228537,0.00003202803,0.00087994663,0.00009753958,0.002897604,0.0006363002,0.00016458491,0.000010854534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010665599,0.00015572291,0.03133491,0.000041048894,0.0000551828,0.0000029921016,0.0012670102,0.17524584,0.00055428455,0.0012612999,0.00012183066,0.78889334],"study_design_scores_gemma":[0.0013238661,0.00023644132,0.005104512,0.00012961864,0.000047158166,0.000041397376,0.00070353475,0.98649037,0.000027192942,0.0008150952,0.0049764635,0.000104331426],"about_ca_topic_score_codex":0.001253396,"about_ca_topic_score_gemma":0.016320515,"teacher_disagreement_score":0.81124455,"about_ca_system_score_codex":0.0003288146,"about_ca_system_score_gemma":0.00056031113,"threshold_uncertainty_score":0.9107231},"labels":[],"label_agreement":null},{"id":"W2890003877","doi":"10.23889/ijpds.v3i4.754","title":"Provincial Data-linkage to Address Complex Policy Challenges","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Government of British Columbia","funders":"","keywords":"Government (linguistics); Analytics; Business; Public relations; Presentation (obstetrics); Public policy; Data science; Economics; Computer science; Political science; Economic growth","score_opus":0.3449094083203832,"score_gpt":0.5399191026791207,"score_spread":0.1950096943587375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890003877","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1681599,0.00036448843,0.023960102,0.70912564,0.043988656,0.003062618,0.017531458,0.00034033414,0.033466797],"genre_scores_gemma":[0.9732041,0.00023787464,0.0084112035,0.0049612694,0.012197889,0.0000066590483,0.00056917244,0.000010882892,0.0004009467],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971987,0.00007254074,0.00038612937,0.00044204117,0.0014193401,0.000481272],"domain_scores_gemma":[0.99774027,0.00015128918,0.00020460763,0.00060139864,0.00090121763,0.00040121694],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0038760582,0.00008856472,0.00011949679,0.0003600257,0.0017396567,0.00069927325,0.005498052,0.000044311557,0.00013775713],"category_scores_gemma":[0.005931302,0.00008140646,0.00002502176,0.00034524556,0.00039494608,0.0033306205,0.0010028156,0.000104425235,0.00003390393],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014214798,0.00012943005,0.017455917,0.000026666528,0.00003688519,0.000007752171,0.0056651295,0.00003128286,0.00007930587,0.6574736,0.08308207,0.23586981],"study_design_scores_gemma":[0.00023522205,0.000039149865,0.16617444,0.000044356835,0.000004758429,0.0000097614275,0.00070066884,0.002385546,0.0000054437805,0.003115449,0.8271532,0.00013201608],"about_ca_topic_score_codex":0.01135348,"about_ca_topic_score_gemma":0.025680877,"teacher_disagreement_score":0.8050442,"about_ca_system_score_codex":0.0003420793,"about_ca_system_score_gemma":0.0013136888,"threshold_uncertainty_score":0.9998827},"labels":[],"label_agreement":null},{"id":"W2890008598","doi":"10.23889/ijpds.v3i4.686","title":"Using Administrative Data to Evaluate the Effectiveness of Home Visiting Programs for Improving the Well-Being of First Nations Children and Parents","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; First Nations Health and Social Secretariat of Manitoba; Manitoba Health","funders":"","keywords":"Welfare; Population; Cohort; General partnership; Medicine; Demography; Psychology; Environmental health; Political science; Business; Sociology; Finance","score_opus":0.11488145981793633,"score_gpt":0.46573827946527524,"score_spread":0.3508568196473389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890008598","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98189294,0.0000199876,0.014631196,0.0003276346,0.0013081494,0.0013299596,0.00024918493,0.000005297676,0.00023564318],"genre_scores_gemma":[0.99459475,0.00003641284,0.0045200787,0.000009862859,0.0006298359,0.000004494661,0.00018764428,0.0000049673613,0.000011955204],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9982909,0.00018262978,0.00034709225,0.00026314732,0.0007103081,0.00020591303],"domain_scores_gemma":[0.9969146,0.00089841266,0.00036295142,0.00032384976,0.0014316594,0.00006853017],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.009381065,0.00006596214,0.00009092258,0.00015438808,0.0071181296,0.00027363337,0.0019768924,0.000024679446,0.0000033173997],"category_scores_gemma":[0.0008094309,0.00004070818,0.000022004964,0.00037746708,0.00052995794,0.0013839031,0.000060048802,0.00006078067,2.9832358e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059211097,0.00039555345,0.3710485,0.00017349381,0.0002513583,3.684368e-7,0.16180035,0.00053730735,0.0007226661,0.44748232,0.000040254617,0.016955694],"study_design_scores_gemma":[0.0017911621,0.0006887744,0.84295654,0.0012517718,0.0002649916,0.000074002455,0.013803068,0.10106728,0.0018525531,0.025039434,0.01066421,0.00054620433],"about_ca_topic_score_codex":0.01486215,"about_ca_topic_score_gemma":0.10082299,"teacher_disagreement_score":0.47190803,"about_ca_system_score_codex":0.00012739903,"about_ca_system_score_gemma":0.0021507416,"threshold_uncertainty_score":0.9941745},"labels":[],"label_agreement":null},{"id":"W2890014696","doi":"10.23889/ijpds.v3i4.993","title":"Measuring social determinants of health and their impact on service use and medical complexity","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Leverage (statistics); Social determinants of health; Population; Government (linguistics); Census; Gerontology; Medicine; Psychology; Environmental health; Public health; Nursing; Computer science","score_opus":0.4097150250298322,"score_gpt":0.5204460008576248,"score_spread":0.11073097582779262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890014696","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98976946,0.000026124138,0.00040370726,0.00871467,0.00077030895,0.00009587403,0.00018227757,0.000006211184,0.00003139243],"genre_scores_gemma":[0.99728835,0.00007883534,0.00043825686,0.0017435923,0.00042502154,5.923952e-7,0.000016050737,0.0000028825616,0.0000064295064],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99837524,0.000094951705,0.0003156854,0.0001650129,0.00082444504,0.0002246946],"domain_scores_gemma":[0.99870133,0.00021476726,0.00025770406,0.00008857074,0.0004811056,0.00025650187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003680823,0.000059805658,0.00013420125,0.0001129924,0.0012960725,0.00026050894,0.0006513237,0.000031976477,0.000029057588],"category_scores_gemma":[0.0020497392,0.00004264462,0.000019141064,0.0001340396,0.000520917,0.0013945078,0.00017209524,0.000077939294,5.362917e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009505726,0.000039697698,0.89293814,0.00002505917,0.000013510435,7.4679775e-7,0.0069915485,0.0000014359929,0.0000061595047,0.017279224,0.00052973663,0.08207968],"study_design_scores_gemma":[0.00024233741,0.000053657535,0.9879125,0.0001100709,0.0000013235376,0.000014272737,0.0009022891,0.0060351575,0.0000061402006,0.002330107,0.0023374064,0.00005476096],"about_ca_topic_score_codex":0.012790324,"about_ca_topic_score_gemma":0.009669697,"teacher_disagreement_score":0.09497433,"about_ca_system_score_codex":0.00013154256,"about_ca_system_score_gemma":0.0006850644,"threshold_uncertainty_score":0.9968473},"labels":[],"label_agreement":null},{"id":"W2890039290","doi":"10.23889/ijpds.v3i4.647","title":"Power of Linked Administrative Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Subsidy; Service (business); Intervention (counseling); Political science; Business; Medicine; Nursing","score_opus":0.21305899722917543,"score_gpt":0.5135269404990472,"score_spread":0.3004679432698718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890039290","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7555575,0.000103549915,0.1577998,0.01593399,0.01758946,0.00083117903,0.0126223555,0.00009040325,0.039471764],"genre_scores_gemma":[0.9866961,0.00002991737,0.011436326,0.00009717133,0.00084284646,6.183143e-7,0.00066181633,0.0000034417671,0.00023172749],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99794537,0.000054499647,0.00036129475,0.00032244195,0.0011316813,0.00018471012],"domain_scores_gemma":[0.9978805,0.00014313753,0.00037646168,0.0006416956,0.0008437934,0.00011441231],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.003639573,0.000056004028,0.0000933477,0.0002175118,0.0007888042,0.00040987422,0.0055470536,0.000020607264,0.00028981522],"category_scores_gemma":[0.0036133148,0.000049003167,0.000028714356,0.00034180586,0.00075642,0.004467048,0.0007874961,0.00007489231,0.000009562428],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034257784,0.000598076,0.15903386,0.000010226417,0.00045813693,0.00001651683,0.017239312,0.00006269756,0.00809134,0.5284763,0.061533168,0.22413777],"study_design_scores_gemma":[0.0007583961,0.00022361027,0.18748154,0.00016312588,0.0000663161,0.00002767115,0.0055605965,0.039685424,0.00029695846,0.01867092,0.7466542,0.00041125962],"about_ca_topic_score_codex":0.00048176598,"about_ca_topic_score_gemma":0.0012094844,"teacher_disagreement_score":0.685121,"about_ca_system_score_codex":0.00005312133,"about_ca_system_score_gemma":0.00047264775,"threshold_uncertainty_score":0.9998334},"labels":[],"label_agreement":null},{"id":"W2890048049","doi":"10.23889/ijpds.v3i4.657","title":"Data Linkage for Optimizing Rectal Cancer Care in Alberta","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Medicine; Colorectal cancer; Grading (engineering); Multidisciplinary approach; Family medicine; Linkage (software); Data extraction; MEDLINE; Cancer; Medical physics; Internal medicine","score_opus":0.43988751224442263,"score_gpt":0.6094285896483009,"score_spread":0.1695410774038783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890048049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71151197,0.00032894893,0.18336293,0.06656132,0.02421866,0.0032333275,0.010066707,0.00006358429,0.0006525712],"genre_scores_gemma":[0.8894634,0.00007991187,0.10030243,0.001193846,0.002790618,0.000017059712,0.0060125366,0.000015982861,0.00012421464],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99779475,0.00002239164,0.0008011081,0.000491708,0.0006702632,0.0002197717],"domain_scores_gemma":[0.99689734,0.00055721053,0.00040660793,0.00062413054,0.0014009444,0.000113744994],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0023184204,0.000088401976,0.00013551631,0.0002739137,0.0002325755,0.00020888945,0.0015975496,0.000040601004,0.00009445247],"category_scores_gemma":[0.013460852,0.000080052014,0.000032929744,0.0002463741,0.00011179538,0.0034104537,0.00053902034,0.00015834208,0.0000057881607],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004061379,0.00036232275,0.27354696,0.00009394,0.00020589867,0.000021723425,0.0013952518,0.0010892092,0.006400997,0.0022349327,0.038590953,0.6719964],"study_design_scores_gemma":[0.0071987193,0.00059774064,0.109564066,0.0005246105,0.00018209103,0.0002768203,0.0011748662,0.61743385,0.0005178257,0.0010920654,0.26107687,0.00036049008],"about_ca_topic_score_codex":0.0021811281,"about_ca_topic_score_gemma":0.011252373,"teacher_disagreement_score":0.6716359,"about_ca_system_score_codex":0.00032306212,"about_ca_system_score_gemma":0.00059961766,"threshold_uncertainty_score":0.9948492},"labels":[],"label_agreement":null},{"id":"W2890057771","doi":"10.23889/ijpds.v3i4.691","title":"Validating health conditions in a clinical registry using administrative data algorithms","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Trinity Western University; University of Calgary; University of Manitoba","funders":"","keywords":"Medicine; Medical record; Population; Disease registry; Confidence interval; Medical prescription; Cohort; Diagnosis code; Emergency medicine; Physical therapy; Internal medicine; Disease; Environmental health","score_opus":0.872403365205847,"score_gpt":0.675343346029787,"score_spread":0.19706001917606009,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890057771","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53029287,0.00043802123,0.33720654,0.07874029,0.020661999,0.0017577825,0.029812543,0.000075151336,0.001014787],"genre_scores_gemma":[0.86928916,0.000062219966,0.11940167,0.005333373,0.0031007584,0.000009830792,0.0026901048,0.000020306896,0.000092576585],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9935802,0.00022967863,0.004600139,0.00088081276,0.00033752783,0.0003716322],"domain_scores_gemma":[0.99332714,0.00071541703,0.004125405,0.0011762384,0.0004032339,0.00025254342],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.045137662,0.0001239879,0.00044781348,0.00053810526,0.00068496744,0.0005074923,0.0031140335,0.00006765303,0.00013740202],"category_scores_gemma":[0.01881131,0.00015145901,0.000048742506,0.00035836632,0.00035693648,0.0051403423,0.00054110226,0.00024959512,0.0000839319],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009957927,0.00057700387,0.7169387,0.00008242213,0.00019370152,0.000010297092,0.0015643145,0.00082371716,0.00002583322,0.20286572,0.06934773,0.007470994],"study_design_scores_gemma":[0.001324683,0.0001597345,0.18716836,0.00028133433,0.0000057814277,0.00015381291,0.0010554716,0.7507324,0.0000032646094,0.025222123,0.033557557,0.00033545692],"about_ca_topic_score_codex":0.0016212189,"about_ca_topic_score_gemma":0.00077171286,"teacher_disagreement_score":0.7499087,"about_ca_system_score_codex":0.0008642122,"about_ca_system_score_gemma":0.0012118134,"threshold_uncertainty_score":0.9894537},"labels":[],"label_agreement":null},{"id":"W2890064903","doi":"10.23889/ijpds.v3i4.1002","title":"Design and operation of a distributed health data network","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Confidentiality; Data quality; Data governance; Data science; Computer security; Process management; Business","score_opus":0.747816945178248,"score_gpt":0.6736739801273999,"score_spread":0.07414296505084816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890064903","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017155081,0.00010365526,0.9659467,0.014396427,0.0013670371,0.00040391317,0.0005845169,0.000010654346,0.000032035077],"genre_scores_gemma":[0.8395396,0.00030438002,0.15705492,0.000524997,0.0009278688,0.000001528232,0.0015905547,0.000005876766,0.000050310235],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99762785,0.000057529836,0.00051471934,0.00034665162,0.0012742077,0.00017901519],"domain_scores_gemma":[0.9962646,0.0009846495,0.00028615855,0.00069786655,0.0015915664,0.00017521101],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.013310676,0.0000517126,0.00012523233,0.00011508352,0.00032112942,0.00015681652,0.0015693542,0.00004476151,0.00003291612],"category_scores_gemma":[0.013523555,0.00004203136,0.000011695471,0.00022562571,0.0004509533,0.0012278782,0.00085062714,0.00027237332,0.0000025084819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0057121105,0.0010626329,0.3117779,0.0003076446,0.00055814657,0.00003248013,0.0009287248,0.008291293,0.008275052,0.21395689,0.12201916,0.32707798],"study_design_scores_gemma":[0.0013380129,0.00077386166,0.119619995,0.000417969,0.000021158108,0.0001989614,0.000043338052,0.8432518,0.00017509765,0.027421735,0.0066398773,0.00009818943],"about_ca_topic_score_codex":0.00009991765,"about_ca_topic_score_gemma":0.00010193691,"teacher_disagreement_score":0.8349605,"about_ca_system_score_codex":0.00009148233,"about_ca_system_score_gemma":0.0010389672,"threshold_uncertainty_score":0.99478596},"labels":[],"label_agreement":null},{"id":"W2890066067","doi":"10.23889/ijpds.v3i4.688","title":"When does the increased mortality risk appear in rheumatoid arthritis? A distributed data analysis comparing mortality in two Canadian provinces","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Rheumatoid Arthritis Research and Therapies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Research Canada; McGill University","funders":"","keywords":"Medicine; Rheumatoid arthritis; Hazard ratio; Proportional hazards model; Cohort; Internal medicine; Demography; Population; Mortality rate; Risk of mortality; Cohort study; Confidence interval; Environmental health","score_opus":0.06873438678034134,"score_gpt":0.40393363534573723,"score_spread":0.3351992485653959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890066067","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9923702,0.00024446167,0.002278042,0.0009724167,0.0003685226,0.0003810354,0.0033092585,0.000012267615,0.00006379619],"genre_scores_gemma":[0.99371606,0.00124449,0.0008404602,0.000070426315,0.00015138251,0.000010328819,0.003957082,0.0000064360206,0.0000033060612],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99709046,0.00015112091,0.0006593129,0.0005224801,0.0011632496,0.00041335917],"domain_scores_gemma":[0.9978028,0.00013305251,0.0002815049,0.0010398437,0.00045187515,0.00029093382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053453655,0.000121170786,0.0002739686,0.0007628589,0.0004951863,0.00058985496,0.0024344588,0.000025395293,0.00012645291],"category_scores_gemma":[0.003301012,0.0000815679,0.00004951342,0.00087095535,0.0005213884,0.0022749722,0.00046780708,0.00030432368,0.0000053199674],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000083113344,0.000059593724,0.9921684,0.0000017873285,0.00017053692,0.000021157943,0.00014830401,0.00010033555,0.000024208644,0.0004390121,0.00014403857,0.0066394648],"study_design_scores_gemma":[0.0010463395,0.000018611487,0.7977022,0.00014561493,0.000010618,0.00003705367,0.00017217902,0.19769928,0.000016401262,0.0017312015,0.0013381612,0.00008236936],"about_ca_topic_score_codex":0.56575495,"about_ca_topic_score_gemma":0.9447495,"teacher_disagreement_score":0.37899455,"about_ca_system_score_codex":0.00035690307,"about_ca_system_score_gemma":0.00086357235,"threshold_uncertainty_score":0.5687985},"labels":[],"label_agreement":null},{"id":"W2890074439","doi":"10.23889/ijpds.v3i4.626","title":"Primary health care engagement among marginalized people who use drugs in Ottawa, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"BC Centre for Disease Control; Bruyère; University of Ottawa; Ottawa Public Health; University of Toronto; St. Michael's Hospital; McGill University; Institute for Clinical Evaluative Sciences; Ottawa Hospital","funders":"","keywords":"Medicine; Family medicine; Odds ratio; Confidence interval; Logistic regression; Primary care; Population; Cohort; Health care; Emergency department; Demography; Nursing; Environmental health; Internal medicine","score_opus":0.06234570385215394,"score_gpt":0.3880181742536709,"score_spread":0.325672470401517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890074439","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98570234,0.000120211465,0.0014700948,0.0070588207,0.0028134775,0.00075351517,0.00042639254,0.000026211777,0.0016289108],"genre_scores_gemma":[0.9939686,0.00004035457,0.002348388,0.001480822,0.00042784965,0.000009459169,0.0012977496,0.000010641125,0.00041614418],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99748045,0.000041596762,0.00046357536,0.0003661241,0.0013499544,0.00029830667],"domain_scores_gemma":[0.99854213,0.00005794697,0.00027837278,0.0004027842,0.0005289799,0.00018976873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001099745,0.00011017858,0.00018103853,0.00035317612,0.0003163288,0.00033290012,0.0008894492,0.000015985035,0.00013928255],"category_scores_gemma":[0.00041961047,0.0001029156,0.000031060088,0.00033150718,0.00012846458,0.002000312,0.00033256467,0.00014136246,0.0000024612366],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043584645,0.00016900578,0.80162895,0.00018094038,0.000114272014,0.000053006093,0.0028038805,0.00037360843,0.000048274385,0.0066466755,0.16785397,0.019691559],"study_design_scores_gemma":[0.0014029777,0.00006446181,0.9419655,0.00017166769,0.000016342128,0.00001652002,0.0011409097,0.0047101844,0.0000064029805,0.00008590349,0.05031528,0.0001038596],"about_ca_topic_score_codex":0.2292392,"about_ca_topic_score_gemma":0.3752855,"teacher_disagreement_score":0.14604631,"about_ca_system_score_codex":0.0024272432,"about_ca_system_score_gemma":0.0026567485,"threshold_uncertainty_score":0.7758934},"labels":[],"label_agreement":null},{"id":"W2890154821","doi":"10.23889/ijpds.v3i4.797","title":"A Data Science Approach to Predictive Analytic Research and Knowledge Translation","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute for Clinical Evaluative Sciences; Ottawa Hospital; Bruyère; University of Ottawa","funders":"","keywords":"Computer science; Workflow; Documentation; Predictive analytics; Data pre-processing; Data mining; Machine learning; Data science; Software engineering; Database; Programming language","score_opus":0.40052256387633967,"score_gpt":0.5098085123995284,"score_spread":0.10928594852318874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890154821","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68893677,0.000057475703,0.28557733,0.0024782869,0.001804107,0.001610011,0.0012136431,0.000046484027,0.01827588],"genre_scores_gemma":[0.9709758,0.000030803192,0.02810232,0.00015183071,0.0004233541,0.000011617348,0.0001951987,0.000011174285,0.00009788733],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9953635,0.00008899027,0.0003943112,0.0013848024,0.0022224851,0.0005459145],"domain_scores_gemma":[0.99782664,0.00021747834,0.00014709687,0.0010225733,0.00035417287,0.00043202948],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.013431446,0.000121256904,0.00010887341,0.00063995324,0.0016865928,0.00060962234,0.0046624583,0.000036355465,0.000084541905],"category_scores_gemma":[0.0025806916,0.00011212087,0.000012707366,0.0016221053,0.0024556841,0.00803373,0.0028641704,0.00026429744,0.00010765857],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070753496,0.0014663738,0.21174736,0.00003607679,0.00009024986,0.000010705613,0.010627341,0.0031144575,0.050817706,0.0074098674,0.011468801,0.7025035],"study_design_scores_gemma":[0.00047989743,0.00024801146,0.3428121,0.000052544972,0.000013294255,0.00008634269,0.00042694196,0.6270357,0.00030044306,0.002372452,0.025956469,0.00021581863],"about_ca_topic_score_codex":0.00028920147,"about_ca_topic_score_gemma":0.00022535208,"teacher_disagreement_score":0.7022877,"about_ca_system_score_codex":0.0007033976,"about_ca_system_score_gemma":0.0002698887,"threshold_uncertainty_score":0.99961305},"labels":[],"label_agreement":null},{"id":"W2890154997","doi":"10.23889/ijpds.v3i4.716","title":"Patient-Reported Outcomes Improves the Prediction of In-patient and Emergency Department Readmission Risks in Coronary Artery Disease","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Lethbridge; University of Alberta; University of Calgary","funders":"","keywords":"Medicine; Emergency department; Logistic regression; Coronary artery disease; Emergency medicine; Angina; Prom; Population; Statistic; Ambulatory; Myocardial infarction; Internal medicine; Statistics","score_opus":0.10482861603763223,"score_gpt":0.4326296209606757,"score_spread":0.3278010049230435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890154997","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9936322,0.00006330226,0.0003080027,0.0029757416,0.002202181,0.0005682061,0.00022045047,0.00000548123,0.000024446455],"genre_scores_gemma":[0.998988,0.000082687766,0.00042515507,0.00016068658,0.00013912305,0.000013543461,0.00017577938,0.0000045704533,0.000010480022],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99800533,0.00004833144,0.00084138353,0.00023839324,0.00070173177,0.00016480374],"domain_scores_gemma":[0.99863094,0.000049199905,0.000379754,0.00027596965,0.00044505383,0.00021909298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011544861,0.00007161024,0.00012585922,0.0002916235,0.00014130221,0.000028579687,0.00020972305,0.00002715617,0.00002009614],"category_scores_gemma":[0.0012043453,0.000045922327,0.000023674735,0.00020881943,0.000082117025,0.0007112391,0.00010972427,0.000110729474,4.5354793e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020274371,0.000093986906,0.9300766,0.000015980626,0.000010167115,0.000012565593,0.00027879703,0.0000063329944,0.00015512985,0.00014313355,0.00020944724,0.06879513],"study_design_scores_gemma":[0.0005257769,0.00025257858,0.98776716,0.00014922791,0.0000070016886,0.00012628415,0.00014899309,0.008965668,0.000011504955,0.00049802626,0.0015119297,0.00003582829],"about_ca_topic_score_codex":0.00125918,"about_ca_topic_score_gemma":0.000342254,"teacher_disagreement_score":0.0687593,"about_ca_system_score_codex":0.00017564141,"about_ca_system_score_gemma":0.00052445213,"threshold_uncertainty_score":0.1903512},"labels":[],"label_agreement":null},{"id":"W2890158550","doi":"10.23889/ijpds.v3i4.672","title":"Mortality attributable to poor dietary patterns in Canada: Evidence from the nationally-representative nutrition survey linked with health administrative data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Statistics Canada; Ottawa Hospital; Bruyère; University of Ottawa","funders":"","keywords":"Medicine; Environmental health; Dash; National Health and Nutrition Examination Survey; Population; Mediterranean diet; Demography; Hazard ratio; Gerontology; Confidence interval","score_opus":0.39209126305338293,"score_gpt":0.49241575206279165,"score_spread":0.10032448900940871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890158550","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92251986,0.00021027087,0.0063353395,0.040701695,0.0009841541,0.0010140657,0.0282105,0.0000088389115,0.000015260961],"genre_scores_gemma":[0.98205996,0.00015051795,0.0037979293,0.0024196396,0.0007851392,0.000025294505,0.010737496,0.0000074824225,0.000016518212],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968288,0.0001106468,0.00053138443,0.0005989709,0.0016558983,0.00027429734],"domain_scores_gemma":[0.99653184,0.0007331907,0.00031935834,0.0005837025,0.0016251825,0.00020674878],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022226344,0.00012929944,0.00022126872,0.00010495145,0.0005038352,0.00016963911,0.0016538013,0.000019267729,0.00006255941],"category_scores_gemma":[0.0026353858,0.00009028198,0.000019261457,0.00047493892,0.00015643933,0.0016541732,0.0005789491,0.000184003,0.0000031458724],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078899175,0.00013883399,0.9729655,0.000007830469,0.00009131903,0.00001503954,0.00009888982,0.000040515006,0.00004902714,0.00007364723,0.024885057,0.00084538496],"study_design_scores_gemma":[0.00086548034,0.00023649828,0.9903219,0.0005030329,0.000016642702,0.00003365809,0.00054774527,0.005735295,0.000034132918,0.00018822069,0.0014147112,0.00010268945],"about_ca_topic_score_codex":0.8191499,"about_ca_topic_score_gemma":0.95832497,"teacher_disagreement_score":0.13917503,"about_ca_system_score_codex":0.0010454248,"about_ca_system_score_gemma":0.0029567801,"threshold_uncertainty_score":0.5245201},"labels":[],"label_agreement":null},{"id":"W2890159467","doi":"10.23889/ijpds.v3i4.873","title":"Emergency Department Use in Patients with Cancer: A Population-Based Study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Neutropenia and Cancer Infections","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; Alberta Health Services","funders":"","keywords":"Medicine; Emergency department; Cancer; Cancer registry; Lung cancer; Population; Ambulatory; Breast cancer; Medical record; Emergency medicine; Outpatient clinic; Internal medicine; Pediatrics","score_opus":0.06420667643616902,"score_gpt":0.4068408924129251,"score_spread":0.3426342159767561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890159467","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9957465,0.000005196454,0.0008516533,0.00033034882,0.0021316635,0.00066449656,0.00023059739,0.000015258422,0.000024289526],"genre_scores_gemma":[0.9978316,0.000004291361,0.0010631557,0.00015164194,0.00034368446,0.00003823182,0.00049038086,0.000010450059,0.00006656946],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981772,0.000020900157,0.00037380305,0.00033402926,0.00091072737,0.00018335476],"domain_scores_gemma":[0.9983282,0.000022087897,0.00020857077,0.00032404484,0.00100381,0.00011328054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037362933,0.000096949596,0.00011783846,0.00038863163,0.0002890665,0.00013631229,0.00045919267,0.00001754263,0.00020375501],"category_scores_gemma":[0.00020234258,0.000075161115,0.000026058791,0.0004466114,0.00004252386,0.001602339,0.000074508425,0.00009776213,0.0000044158323],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044063252,0.00043832036,0.99607015,0.0000019278107,0.000027044267,0.0000024402163,0.000027182943,0.00027115952,0.000017757102,0.00007048108,0.00048326177,0.0021496678],"study_design_scores_gemma":[0.0024651205,0.00051787996,0.9936185,0.000051266186,0.000037372734,0.000004860945,0.00001554524,0.0017332198,0.000016450444,0.000036455796,0.0014138058,0.00008950751],"about_ca_topic_score_codex":0.0016242962,"about_ca_topic_score_gemma":0.005274697,"teacher_disagreement_score":0.003650401,"about_ca_system_score_codex":0.00043726317,"about_ca_system_score_gemma":0.00024522096,"threshold_uncertainty_score":0.30649814},"labels":[],"label_agreement":null},{"id":"W2890164357","doi":"10.23889/ijpds.v3i4.683","title":"Extending follow up of randomised clinical trials by linkage to routinely collected data – results of a scoping review of the published literature","year":2018,"lang":"en","type":"review","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Ontario Council of University Libraries; University of Toronto","funders":"","keywords":"Linkage (software); Medicine; Record linkage; Data extraction; Protocol (science); Family medicine; MEDLINE; Data mining; Alternative medicine; Computer science; Population; Environmental health; Pathology","score_opus":0.7130505119794814,"score_gpt":0.6578263544840742,"score_spread":0.05522415749540721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890164357","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000016098917,0.9040352,0.016931932,0.0016490809,0.012697184,0.005380107,0.0591117,0.000010037998,0.00016867193],"genre_scores_gemma":[0.000056033234,0.98530626,0.0049856096,0.00025567645,0.0005239748,0.000021365753,0.008193376,0.000014529994,0.00064315234],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.97782403,0.003417325,0.0117543535,0.0013747064,0.005352889,0.0002766891],"domain_scores_gemma":[0.9504332,0.014804444,0.022135898,0.006266248,0.006081692,0.00027853608],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.19478796,0.00027763494,0.0028324085,0.00097373076,0.00025493823,0.001147516,0.023959046,0.00015217077,0.000099471385],"category_scores_gemma":[0.51064634,0.00015433376,0.0007767383,0.0036656163,0.00035823352,0.0038582676,0.0055816215,0.00037362133,0.000004325271],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009214435,0.0001311962,0.00002030359,0.0075529628,0.00028338545,0.0000012589243,0.00007132835,0.000002892013,0.0000051830816,0.0004802888,0.4760178,0.51451194],"study_design_scores_gemma":[0.0039058377,0.00007096185,0.00003946376,0.28961495,0.0004085668,0.000016989303,0.000018141602,0.00048986,0.000004668429,0.00044651795,0.70480424,0.00017978775],"about_ca_topic_score_codex":0.000044202832,"about_ca_topic_score_gemma":0.000048660655,"teacher_disagreement_score":0.5143322,"about_ca_system_score_codex":0.000091110465,"about_ca_system_score_gemma":0.0015462901,"threshold_uncertainty_score":0.9998894},"labels":[],"label_agreement":null},{"id":"W2890168788","doi":"10.23889/ijpds.v3i4.790","title":"Characteristics of Opioid-Related Deaths in Ontario, Canada: Leveraging the Drug and Drug/Alcohol Related Death (DDARD) Database","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ontario Drug Policy Research Network; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Opioid; Coroner; Cause of death; Socioeconomic status; Drug; Poison control; Injury prevention; Environmental health; Psychiatry; Population; Disease; Internal medicine","score_opus":0.0407405512593436,"score_gpt":0.3311188546370106,"score_spread":0.29037830337766696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890168788","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99568146,0.0000803582,0.00013451229,0.0019320817,0.0014102334,0.00031027573,0.00030807228,0.000007069492,0.00013591877],"genre_scores_gemma":[0.9970369,0.00005700496,0.00139362,0.00017820743,0.00007054709,0.000004295784,0.000888178,0.00000962573,0.00036162874],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980677,0.000028814618,0.0005815203,0.00031283838,0.0008040121,0.0002051104],"domain_scores_gemma":[0.99856764,0.00009573512,0.0003346863,0.00039693015,0.0004951049,0.00010991528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010267989,0.00011778915,0.00017284909,0.00023036281,0.00024615382,0.000088086905,0.00068019057,0.000022734306,0.000090554204],"category_scores_gemma":[0.00044930293,0.000086840686,0.000025093055,0.00021527443,0.00016252011,0.00075647986,0.00026368353,0.00023380455,0.0000014742825],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011366308,0.000086613334,0.99289477,0.000009293309,0.00007153134,0.000031616095,0.0014521433,0.000018860377,0.00034193313,0.0012382949,0.0009093447,0.0028319175],"study_design_scores_gemma":[0.0012987688,0.0000313254,0.9867759,0.00022289419,0.00005707957,0.00020047578,0.00019365811,0.008358747,0.00016728845,0.0004723982,0.0021319215,0.00008954289],"about_ca_topic_score_codex":0.6568571,"about_ca_topic_score_gemma":0.5659205,"teacher_disagreement_score":0.090936616,"about_ca_system_score_codex":0.00070202095,"about_ca_system_score_gemma":0.0016996858,"threshold_uncertainty_score":0.44200036},"labels":[],"label_agreement":null},{"id":"W2890205989","doi":"10.23889/ijpds.v3i4.1028","title":"Using Linked Data and Advanced Analytics to Prioritize Health Concerns within Regions","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Data science; Population; Computer science; Health indicator; Public health; Decision support system; Population health; Analytics; Disease surveillance; Data mining; Environmental health; Medicine","score_opus":0.2669284483601198,"score_gpt":0.5166225883596763,"score_spread":0.24969413999955653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890205989","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68725413,0.00024299754,0.27499285,0.01709267,0.0061684,0.0013134863,0.012670736,0.00011453337,0.00015018169],"genre_scores_gemma":[0.8674854,0.000057938447,0.12745957,0.0017359918,0.0010507369,0.0000015400465,0.0021127323,0.000014059513,0.000082038714],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997757,0.000029572562,0.0005144633,0.0005713501,0.0008778695,0.00024974282],"domain_scores_gemma":[0.99713004,0.00006284633,0.00037951794,0.0010454339,0.00093922456,0.00044295617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001668257,0.00010741553,0.00019504642,0.00029646454,0.00043154162,0.0002600647,0.0016383328,0.00002400974,0.00001892824],"category_scores_gemma":[0.0028185798,0.00009861868,0.000020230578,0.00039594254,0.00027697912,0.0019960916,0.0009472956,0.000127931,0.000006209751],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037800085,0.00076387683,0.60513157,0.00020128075,0.00071688945,0.00017173449,0.0025096452,0.0033886184,0.0230042,0.026867913,0.07833446,0.2551298],"study_design_scores_gemma":[0.0026637802,0.0004143366,0.2473095,0.0006890232,0.00007635304,0.000816208,0.00032048658,0.66984344,0.000070067974,0.001508705,0.07593457,0.00035352327],"about_ca_topic_score_codex":0.00014646433,"about_ca_topic_score_gemma":0.00028732623,"teacher_disagreement_score":0.6664548,"about_ca_system_score_codex":0.0002583172,"about_ca_system_score_gemma":0.0007953776,"threshold_uncertainty_score":0.4021553},"labels":[],"label_agreement":null},{"id":"W2890208673","doi":"10.23889/ijpds.v3i4.662","title":"Creating the Framework for Cross-Sector Health Analysis for Local Communities","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ministry of Health","funders":"","keywords":"Geocoding; Geography; Population; Work (physics); Christian ministry; Census; Unit (ring theory); Environmental planning; Environmental health; Political science; Medicine; Cartography; Engineering; Psychology","score_opus":0.3457435316225467,"score_gpt":0.6275113714741626,"score_spread":0.2817678398516159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890208673","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06923816,0.00003626352,0.89432895,0.025124758,0.0083268825,0.0010661336,0.0017363856,0.000028056964,0.00011438611],"genre_scores_gemma":[0.934754,0.000030297771,0.048669722,0.008405615,0.00605475,0.00021378255,0.0014556937,0.000016275586,0.00039983875],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975163,0.00015419934,0.0008939282,0.00024255669,0.00057933317,0.00061372545],"domain_scores_gemma":[0.9930102,0.0026927146,0.0009366955,0.00059569284,0.0025540476,0.00021061744],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008192392,0.00010589627,0.00019732311,0.00038866408,0.008058548,0.0003653278,0.0021908763,0.00007921608,0.00014619685],"category_scores_gemma":[0.004091633,0.00007619649,0.00009797013,0.0005977809,0.00040533702,0.0013222969,0.0002690968,0.00030968463,0.000006702272],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043637914,0.00013510454,0.43733925,0.00015423443,0.00038444783,6.848233e-8,0.023194173,0.001971679,0.000008658715,0.44266,0.060634546,0.033081472],"study_design_scores_gemma":[0.0007451266,0.0002304498,0.34183112,0.00017668288,0.0000554468,0.000005409672,0.0119329505,0.3459266,0.0000032004486,0.036021292,0.2629,0.00017172893],"about_ca_topic_score_codex":0.0056262235,"about_ca_topic_score_gemma":0.0030886398,"teacher_disagreement_score":0.8655159,"about_ca_system_score_codex":0.000641079,"about_ca_system_score_gemma":0.0014938646,"threshold_uncertainty_score":0.99323285},"labels":[],"label_agreement":null},{"id":"W2890221034","doi":"10.23889/ijpds.v3i4.753","title":"The Ontario Data Safe Haven: Bringing High Performance Computing to Population-wide Data Assets","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hospital for Sick Children; University of Toronto; Vector Institute; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Cloud computing; Documentation; Computer science; Data science; Population; Big data; Health care; Dashboard; Computer security; Medicine; Data mining","score_opus":0.43283693025766146,"score_gpt":0.5488237627508102,"score_spread":0.11598683249314878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890221034","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.847376,0.000024293695,0.10543742,0.0200567,0.023771405,0.0010592652,0.001128841,0.00009189674,0.0010541584],"genre_scores_gemma":[0.9659937,0.000025188025,0.022279788,0.0024638234,0.0027767182,0.00000513405,0.0057254853,0.000013493635,0.0007166562],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99574274,0.000113547285,0.0012869529,0.00057784055,0.0016439235,0.00063497975],"domain_scores_gemma":[0.99469006,0.000949468,0.0008683812,0.0020808084,0.0010764434,0.00033486236],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.012301592,0.00014143862,0.00016950264,0.0002754727,0.00654235,0.00043312894,0.007910445,0.00007341057,0.00016235145],"category_scores_gemma":[0.0076288823,0.00010679961,0.000015343205,0.00035208763,0.00013102144,0.0052933325,0.0039074076,0.0006441024,0.00015722717],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002245529,0.000035464367,0.73252094,0.000056012956,0.000041936153,0.000001896769,0.0018782417,0.00073024345,0.000020882188,0.003714717,0.1121199,0.1486552],"study_design_scores_gemma":[0.00029605566,0.000033931447,0.5022443,0.00027255842,0.000008377362,0.000012840356,0.00011300382,0.3266837,0.0000015731746,0.00023141918,0.17000261,0.000099637284],"about_ca_topic_score_codex":0.013604599,"about_ca_topic_score_gemma":0.03133305,"teacher_disagreement_score":0.32595345,"about_ca_system_score_codex":0.0007376965,"about_ca_system_score_gemma":0.00104395,"threshold_uncertainty_score":0.9974572},"labels":[],"label_agreement":null},{"id":"W2890243167","doi":"10.23889/ijpds.v3i4.719","title":"Early Childhood Respiratory Morbidity and Health Services Utilization in Children Born Preterm or Small and Large for Gestational Age","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Neonatal Respiratory Health Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Calgary; University of Alberta","funders":"","keywords":"Medicine; Bronchopulmonary dysplasia; Small for gestational age; Pediatrics; Odds ratio; Pneumonia; Gestational age; Cohort; Obstetrics; Pregnancy; Internal medicine","score_opus":0.19495610449665746,"score_gpt":0.4831850143841829,"score_spread":0.2882289098875254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890243167","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99217755,0.00033112097,0.0040213964,0.0011348857,0.00032458807,0.0011029774,0.0008809534,0.000015236842,0.000011296872],"genre_scores_gemma":[0.9909381,0.00019982837,0.0057831854,0.0018071162,0.0005763254,0.000024357993,0.0006214162,0.000015785577,0.000033861008],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979327,0.000043981716,0.0004829023,0.00045764778,0.00074620696,0.00033656284],"domain_scores_gemma":[0.99845314,0.00010312508,0.0002624117,0.00023759613,0.00065041264,0.00029333594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028428074,0.000108663575,0.00015992466,0.00049593474,0.0004595258,0.00024020621,0.00050637947,0.000049535658,0.000016147751],"category_scores_gemma":[0.00071610155,0.00009187098,0.000016672211,0.00027663598,0.00017926614,0.0013423535,0.00024361229,0.0001614472,0.000001315301],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009216722,0.00018079873,0.8487522,0.0001730707,0.000033394423,0.000009095198,0.0007045415,0.000003801545,0.00023674696,0.0021483554,0.00016772312,0.14666861],"study_design_scores_gemma":[0.0023088765,0.00056016986,0.98512536,0.0002005503,0.0000060969646,0.000113441114,0.000038617836,0.004393103,0.00004482425,0.0005671146,0.0065603782,0.00008145889],"about_ca_topic_score_codex":0.00029481252,"about_ca_topic_score_gemma":0.0011993275,"teacher_disagreement_score":0.14658715,"about_ca_system_score_codex":0.00019944418,"about_ca_system_score_gemma":0.0008527667,"threshold_uncertainty_score":0.37463897},"labels":[],"label_agreement":null},{"id":"W2890248655","doi":"10.23889/ijpds.v3i4.804","title":"Secondary care provision for children and young people with Cerebral palsy: A data-linkage study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cerebral Palsy and Movement Disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Cerebral palsy; Gross Motor Function Classification System; Medicine; Record linkage; Cohort; Pediatrics; Medical record; Outpatient visits; Population; Cohort study; Health care; Physical therapy; Emergency medicine; Internal medicine; Environmental health","score_opus":0.03432642266788842,"score_gpt":0.36450622831838797,"score_spread":0.33017980565049954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890248655","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889902,0.00006284379,0.0063797054,0.0007438621,0.00085334916,0.0014037865,0.001456758,0.000019218727,0.000090277295],"genre_scores_gemma":[0.9893229,0.0000106440575,0.0053601866,0.00022659342,0.0005590687,0.000012261061,0.0044008447,0.0000121634475,0.00009533403],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99833024,0.000013864293,0.00028914938,0.00051181135,0.0006637313,0.00019119353],"domain_scores_gemma":[0.99851876,0.000028665941,0.00019175025,0.0005192124,0.0006228755,0.000118715114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078392937,0.00011101671,0.00014479167,0.00019667433,0.0004817132,0.00028064084,0.00093180017,0.000024565694,0.000044966833],"category_scores_gemma":[0.00032938135,0.00008188282,0.000021066655,0.0001529018,0.00012622208,0.0020115674,0.00043952902,0.00010872352,0.0000015421803],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053364085,0.00016703864,0.96460146,0.000019401843,0.00009155551,0.0000015849112,0.0011845289,0.0000045416673,0.0001506717,0.00020973418,0.0020086088,0.031027205],"study_design_scores_gemma":[0.00403624,0.000993829,0.9869628,0.000072132214,0.00008662764,0.00014680762,0.0014760975,0.0045869374,0.000032309123,0.00016963802,0.0013131982,0.00012338921],"about_ca_topic_score_codex":0.00046141868,"about_ca_topic_score_gemma":0.0034930618,"teacher_disagreement_score":0.030903816,"about_ca_system_score_codex":0.000060124432,"about_ca_system_score_gemma":0.00022572193,"threshold_uncertainty_score":0.37049973},"labels":[],"label_agreement":null},{"id":"W2890249868","doi":"10.23889/ijpds.v3i4.735","title":"Challenges and Facilitating Factors in Accessing Administrative Data for Research: Insights from the Children's Health Profile and Trajectory Initiative in NB and PEI","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick; Cape Breton University; Dalhousie University; Université de Moncton; University of Prince Edward Island","funders":"","keywords":"Custodians; Government (linguistics); Population; Data governance; Corporate governance; Public relations; Medicine; Business; Knowledge management; Political science; Data quality; Computer science; Environmental health; Finance; Geography","score_opus":0.7397469601896688,"score_gpt":0.6473047028404677,"score_spread":0.09244225734920108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890249868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.978682,0.0008229745,0.00032056824,0.016623877,0.0007718245,0.000963826,0.0017226054,0.000005867507,0.00008649697],"genre_scores_gemma":[0.9944628,0.00066363055,0.0027449206,0.0005280865,0.00064788223,0.000037978356,0.00089949457,0.000006441619,0.000008779769],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99773425,0.0004715221,0.00054426794,0.00045815203,0.00042593817,0.00036588407],"domain_scores_gemma":[0.995767,0.003003417,0.00033887313,0.00029343774,0.00043918705,0.00015809384],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005739237,0.0000878684,0.00014421478,0.0003263621,0.0016318294,0.00016371839,0.0008519966,0.000053045875,0.000006655386],"category_scores_gemma":[0.0062881093,0.000062689825,0.0000057451384,0.0002068099,0.00039249638,0.0027331496,0.0005573297,0.00041133008,4.183302e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027801574,0.00014101426,0.56415623,0.00013111325,0.000038866438,6.868516e-7,0.25866756,0.0000037292166,0.00010067339,0.01351134,0.00456303,0.15840772],"study_design_scores_gemma":[0.0005497042,0.00010007075,0.94547546,0.00029220717,0.0000015423151,0.000002595187,0.039900992,0.0066518183,0.0000021849137,0.0045592776,0.0024005463,0.00006360403],"about_ca_topic_score_codex":0.0047149463,"about_ca_topic_score_gemma":0.017806195,"teacher_disagreement_score":0.38131922,"about_ca_system_score_codex":0.00023348963,"about_ca_system_score_gemma":0.0012179558,"threshold_uncertainty_score":0.9996679},"labels":[],"label_agreement":null},{"id":"W2890261961","doi":"10.23889/ijpds.v3i4.1005","title":"Data Linkage and Data Quality Assessment for Congenital Anomalies Surveillance in Ontario","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Newborn Screening Ontario","funders":"","keywords":"Population; Medicine; Data quality; Cohort; Pediatrics; Environmental health; Business; Internal medicine","score_opus":0.65742054997388,"score_gpt":0.6236060878409303,"score_spread":0.033814462132949696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890261961","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81283504,0.000053625794,0.14825237,0.010210395,0.011586542,0.001485372,0.014366122,0.000043382126,0.0011671802],"genre_scores_gemma":[0.9545911,0.000037806494,0.030941833,0.00095111364,0.0010242561,0.000015499301,0.012123358,0.0000067747333,0.00030828035],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99728745,0.0001280918,0.0010109332,0.00047540636,0.00076158857,0.00033653213],"domain_scores_gemma":[0.9965883,0.00077253074,0.00059703045,0.001096915,0.00077238627,0.00017284708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014711683,0.00009010048,0.00016800036,0.00020395339,0.0011166511,0.00016634326,0.0031265558,0.00007160694,0.00011373242],"category_scores_gemma":[0.0049960674,0.00007732802,0.000009731712,0.00012741961,0.00019072815,0.0041700816,0.0016906108,0.00039003888,0.000007282886],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017047973,0.000038864182,0.96529996,0.000059908056,0.00001727656,7.686472e-7,0.0006575409,0.00000522042,0.000031954263,0.006254635,0.01195181,0.015511605],"study_design_scores_gemma":[0.0009648881,0.000050811617,0.7752144,0.0000917383,0.000004417221,0.0000067846236,0.0002586368,0.11198763,5.2463076e-7,0.0012418529,0.11008775,0.00009061779],"about_ca_topic_score_codex":0.013294272,"about_ca_topic_score_gemma":0.24967386,"teacher_disagreement_score":0.23637958,"about_ca_system_score_codex":0.00039025696,"about_ca_system_score_gemma":0.0016222197,"threshold_uncertainty_score":0.9932763},"labels":[],"label_agreement":null},{"id":"W2890268673","doi":"10.23889/ijpds.v3i4.1034","title":"A New Standards-based Grammar for Linking Aggregate Datasets","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Government (linguistics); Interoperability; Aggregate data; Computer science; Human immunodeficiency virus (HIV); Data science; World Wide Web; Medicine; Family medicine","score_opus":0.2856651451075076,"score_gpt":0.5436897848150035,"score_spread":0.2580246397074959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890268673","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024063468,0.000019969119,0.97086686,0.005157493,0.006368364,0.0003566308,0.01466355,0.000025342844,0.00013545806],"genre_scores_gemma":[0.5209284,0.000026058038,0.45420304,0.004531107,0.0054747406,0.000022544438,0.013343772,0.00003281255,0.0014375041],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99383974,0.000059983005,0.00085789134,0.0007237566,0.004183513,0.00033513783],"domain_scores_gemma":[0.994937,0.00060616387,0.00073113217,0.0011261159,0.0023544908,0.000245076],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.016817402,0.00012652889,0.00016277762,0.00066408777,0.0008986755,0.003042957,0.0072095604,0.000035120214,0.00023615472],"category_scores_gemma":[0.013590655,0.00009981559,0.00008018828,0.00061123684,0.0002352058,0.005360054,0.00088546175,0.000096131174,0.00004193466],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004034147,0.000052634678,0.0014439702,0.0000052316545,0.000034644534,0.000004382603,0.000094023504,0.00039314057,0.00023821979,0.044060286,0.37669912,0.5765709],"study_design_scores_gemma":[0.00091715856,0.000112139816,0.0018440813,0.00005280456,0.000014351323,0.0000135051905,0.000058804908,0.071492694,0.00025042694,0.07436355,0.8507395,0.00014098325],"about_ca_topic_score_codex":0.00015981257,"about_ca_topic_score_gemma":0.00050958537,"teacher_disagreement_score":0.57642996,"about_ca_system_score_codex":0.00020193972,"about_ca_system_score_gemma":0.000727983,"threshold_uncertainty_score":0.9981619},"labels":[],"label_agreement":null},{"id":"W2890275127","doi":"10.23889/ijpds.v3i4.751","title":"The Effect of Medication Adherence on the Disease Course in Pregnant Women with Inflammatory Bowel Disease","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Pregnancy and Medication Impact","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Pregnancy; Inflammatory bowel disease; Medical prescription; Ulcerative colitis; Disease; Crohn's disease; Adverse effect; Obstetrics; Internal medicine; Pediatrics","score_opus":0.02773026992451591,"score_gpt":0.37404339226751315,"score_spread":0.34631312234299727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890275127","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99065405,0.00016413904,0.0012840433,0.0061322576,0.0009640501,0.0006296071,0.000098552504,0.000010654867,0.00006264422],"genre_scores_gemma":[0.99915624,0.000102807615,0.00007399384,0.00022607503,0.0002490981,0.000063195635,0.00005211686,0.000006058604,0.000070435155],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99799615,0.000060571492,0.00032795226,0.00021449554,0.0012007536,0.00020009781],"domain_scores_gemma":[0.9979992,0.00043128987,0.00033769573,0.00058678625,0.00034513112,0.0002999232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024547912,0.000087727734,0.00008549403,0.00012452887,0.00031210502,0.00007351092,0.0011001986,0.000016301432,0.000038222264],"category_scores_gemma":[0.0039701005,0.000040734125,0.000022835919,0.00019220138,0.00066931656,0.0006429749,0.0000891085,0.00014202925,0.000005762038],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010983746,0.00022772886,0.8881145,0.00006580704,0.00009702307,0.000029360195,0.0005891495,0.00018232087,0.00038857077,0.0066000447,0.0023990935,0.09032262],"study_design_scores_gemma":[0.0011706362,0.0005529832,0.9831733,0.0013807473,0.00003104364,0.000018491997,0.00005567558,0.011397943,0.00014408426,0.000708675,0.0013090695,0.000057313056],"about_ca_topic_score_codex":0.000010009841,"about_ca_topic_score_gemma":0.000019115947,"teacher_disagreement_score":0.095058806,"about_ca_system_score_codex":0.00016519634,"about_ca_system_score_gemma":0.0007031542,"threshold_uncertainty_score":0.47528678},"labels":[],"label_agreement":null},{"id":"W2890288407","doi":"10.23889/ijpds.v3i4.929","title":"The Shape of the Socioeconomic Gradient: Testing to Functional Form of the Relationship between Socioeconomic Status and Early Child Development","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Saskatchewan; University of Manitoba; Learning Partnership; Manitoba Health; University of British Columbia; McMaster University","funders":"","keywords":"Socioeconomic status; Akaike information criterion; Child development; Psychology; Developmental psychology; Demography; Econometrics; Statistics; Mathematics; Population; Sociology","score_opus":0.09906593759867603,"score_gpt":0.36509296519159784,"score_spread":0.2660270275929218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890288407","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9902194,0.000019868072,0.00018812963,0.006647557,0.0022593634,0.00026512824,0.000041292322,0.0000053278895,0.00035393698],"genre_scores_gemma":[0.9976309,0.00000520803,0.0015508333,0.00015297954,0.00046332835,0.000005167149,0.000009064386,0.0000046451637,0.00017788816],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99844027,0.000053599615,0.00050471525,0.00019605191,0.0005877346,0.0002176141],"domain_scores_gemma":[0.9979859,0.0006005087,0.0005432806,0.00022387014,0.00054298947,0.00010343456],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0025414736,0.000069384914,0.000077291596,0.00010707906,0.0033719228,0.00025625626,0.0014408946,0.000030085765,0.000025133453],"category_scores_gemma":[0.0023680353,0.00004332469,0.00003876111,0.0002098742,0.00068488857,0.0008158447,0.00036777832,0.00012570008,0.000007122037],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006063213,0.000007006688,0.9700774,0.000001061133,0.000013977229,4.300396e-9,0.0056384085,0.000012091745,0.0000053495673,0.016418656,0.00024262481,0.0075773797],"study_design_scores_gemma":[0.00015220743,0.000012243101,0.98312783,0.000037367667,0.0000059542804,0.000001729246,0.0007437708,0.00006876128,0.000037317717,0.008504632,0.007251765,0.00005640334],"about_ca_topic_score_codex":0.00036707718,"about_ca_topic_score_gemma":0.0009188359,"teacher_disagreement_score":0.0130504705,"about_ca_system_score_codex":0.00035236654,"about_ca_system_score_gemma":0.0013083707,"threshold_uncertainty_score":0.9979256},"labels":[],"label_agreement":null},{"id":"W2890297535","doi":"10.23889/ijpds.v3i4.985","title":"Advancing the measurement of health inequalities in Canada with linked health and social data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada; Canadian Institute for Health Information","funders":"","keywords":"Census; Inequality; Population; Cohort; Demography; Medicine; Health equity; Equity (law); Psychological intervention; Record linkage; Socioeconomic status; Geography; Public health; Environmental health; Political science; Mathematics; Sociology","score_opus":0.23094996536151766,"score_gpt":0.4610520679806137,"score_spread":0.23010210261909606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890297535","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5828159,0.0008420135,0.0073523824,0.40111327,0.005254632,0.0009895377,0.0013638743,0.000015860174,0.00025255184],"genre_scores_gemma":[0.9945955,0.0001314147,0.0012618441,0.003576206,0.00034901907,0.0000015997109,0.000072501985,0.0000029544,0.00000891719],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99748504,0.00013247237,0.0004635719,0.00018850902,0.0014234569,0.00030697108],"domain_scores_gemma":[0.99863845,0.00012070764,0.000436282,0.0002071347,0.00048585364,0.000111569534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009413962,0.000049593178,0.00012703043,0.00008570247,0.0012542479,0.0001280749,0.0014348006,0.0000101151645,0.000008670402],"category_scores_gemma":[0.0009776466,0.000034874934,0.0000061246155,0.00018288997,0.00028186964,0.0011821557,0.00022203391,0.00008666758,9.615858e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019266031,0.00005738237,0.67264134,0.00013569146,0.00003937585,0.000001607653,0.033114035,0.000091774695,0.000003792887,0.088548474,0.017589467,0.18758442],"study_design_scores_gemma":[0.00076460134,0.0001106898,0.7877124,0.00036244377,0.000003945758,0.000008584187,0.053439625,0.007302581,0.0000017873866,0.0020214063,0.14811316,0.00015878446],"about_ca_topic_score_codex":0.9289757,"about_ca_topic_score_gemma":0.988924,"teacher_disagreement_score":0.41177964,"about_ca_system_score_codex":0.0011341308,"about_ca_system_score_gemma":0.012642763,"threshold_uncertainty_score":0.9929546},"labels":[],"label_agreement":null},{"id":"W2890298249","doi":"10.23889/ijpds.v3i4.958","title":"Cultural and institutional barriers among data stewards regarding data access for research","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Adjudication; Data access; Legislation; Data Protection Act 1998; Data collection; Business; Public relations; Internet privacy; Computer science; Data science; Sociology; Political science; Database; Computer security; Law","score_opus":0.902046850873375,"score_gpt":0.7456824659560715,"score_spread":0.15636438491730353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890298249","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8486283,0.00026526273,0.08711329,0.033353224,0.011932195,0.0027073377,0.014113363,0.00007416823,0.0018129022],"genre_scores_gemma":[0.961899,0.00031028647,0.02840595,0.0002800879,0.003222876,0.000014551374,0.00550054,0.000014619627,0.00035210553],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9940709,0.00007569197,0.00061673985,0.0010829814,0.0037012312,0.0004524638],"domain_scores_gemma":[0.9851012,0.0036951706,0.0002778657,0.002751531,0.0075107506,0.000663455],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["metaresearch","sts","open_science"],"category_scores_codex":[0.02997212,0.0001091676,0.00017422106,0.0004995559,0.0017111069,0.0015918068,0.010083097,0.0001237339,0.00006905378],"category_scores_gemma":[0.16518688,0.0000863146,0.000027699321,0.00049704185,0.0027237383,0.010549956,0.009007707,0.0009477666,0.000005060175],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003176457,0.0002494504,0.6533932,0.000263765,0.0004863106,0.000060931765,0.0004064817,0.00009491366,0.0032803293,0.10931393,0.12266039,0.10661383],"study_design_scores_gemma":[0.0036454885,0.0004384526,0.28865004,0.00096544594,0.00007693361,0.00046454396,0.00044616367,0.529408,0.0002756707,0.027117541,0.1481835,0.00032827072],"about_ca_topic_score_codex":0.00036055362,"about_ca_topic_score_gemma":0.0007215136,"teacher_disagreement_score":0.529313,"about_ca_system_score_codex":0.00028175913,"about_ca_system_score_gemma":0.0020928674,"threshold_uncertainty_score":0.9999903},"labels":[],"label_agreement":null},{"id":"W2890308754","doi":"10.23889/ijpds.v3i4.986","title":"Advancing data collection of hospital-related harms: Validity of the new ICD-11 Quality &amp; Safety Use Case","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Coding (social sciences); Medicine; Chart; Harm; ICD-10; Medical emergency; Psychology; Statistics; Nursing","score_opus":0.5019121897518046,"score_gpt":0.5732756866141248,"score_spread":0.07136349686232013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890308754","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83465457,0.000011216455,0.13956773,0.008359231,0.014930568,0.0007767273,0.0015148552,0.000027287033,0.00015779548],"genre_scores_gemma":[0.9868758,0.000034805016,0.010986466,0.00041174295,0.00057854207,0.0000025656618,0.0006435241,0.0000067822107,0.00045977486],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99650764,0.00028932656,0.0015622913,0.00026281082,0.0011131283,0.0002648224],"domain_scores_gemma":[0.994348,0.0007845569,0.0019266686,0.0009519001,0.0017981919,0.00019071945],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.009269932,0.000086635366,0.0001776041,0.00019762035,0.001592196,0.000043329695,0.0018583236,0.00008811301,0.00020089354],"category_scores_gemma":[0.019987563,0.00006264189,0.00003679649,0.00053918705,0.0002446295,0.0034749394,0.000816786,0.00035096734,0.000009051362],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005621241,0.0002280522,0.79157406,0.00026340675,0.000067798304,0.0000032995292,0.007057551,0.0003770166,0.00077349064,0.013980285,0.16962755,0.0154853845],"study_design_scores_gemma":[0.0033330298,0.00025558405,0.7030844,0.0013039701,0.00008110866,0.0001993653,0.0012655705,0.11512198,0.00017105792,0.0069229202,0.16793345,0.00032757688],"about_ca_topic_score_codex":0.0052880864,"about_ca_topic_score_gemma":0.00329495,"teacher_disagreement_score":0.1522212,"about_ca_system_score_codex":0.00032566482,"about_ca_system_score_gemma":0.0014199595,"threshold_uncertainty_score":0.9997076},"labels":[],"label_agreement":null},{"id":"W2890311524","doi":"10.23889/ijpds.v3i4.876","title":"Do callers of young children with fever follow the self-care recommendations given by a nursing triage line?","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Medicine; Triage; Family medicine; Health care; Emergency department; Odds ratio; Medical emergency; Odds; Public health; Nursing; Logistic regression","score_opus":0.04997998879165213,"score_gpt":0.3997165376608511,"score_spread":0.34973654886919897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890311524","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9458259,0.000822175,0.017845308,0.025199784,0.0054967008,0.0010459827,0.0020484636,0.00005240611,0.001663331],"genre_scores_gemma":[0.9919564,0.0001829468,0.006497422,0.00015243924,0.0005417922,0.000004534978,0.0005843293,0.0000075360763,0.000072586234],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987114,0.000020067515,0.0002941305,0.00021737318,0.0006182171,0.00013879863],"domain_scores_gemma":[0.99823505,0.000040536837,0.00024583397,0.00026224353,0.0011572143,0.00005910064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048529723,0.000082983766,0.00010951963,0.00013045453,0.0005281591,0.00007561441,0.0006959405,0.000021298978,0.000050750776],"category_scores_gemma":[0.00034714406,0.000051492723,0.000047007718,0.00026332887,0.0002362033,0.0007656795,0.000090910784,0.00011090011,0.0000017206831],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079906144,0.00045838885,0.63729405,0.00001990416,0.0012173111,0.0000048905554,0.00998101,0.00007697884,0.0025096056,0.0027034585,0.25842395,0.08651141],"study_design_scores_gemma":[0.008316596,0.0015724562,0.89989865,0.0016065044,0.00085050566,0.0010093644,0.009132717,0.008637049,0.0025787035,0.0013553243,0.06441115,0.0006309573],"about_ca_topic_score_codex":0.00006832379,"about_ca_topic_score_gemma":0.0000687753,"teacher_disagreement_score":0.26260462,"about_ca_system_score_codex":0.00012737767,"about_ca_system_score_gemma":0.00014435255,"threshold_uncertainty_score":0.40622258},"labels":[],"label_agreement":null},{"id":"W2890312272","doi":"10.23889/ijpds.v3i4.859","title":"International meta-analysis of 684,660 men with vasectomies: a study utilising the International Population Data Linkage Network","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Male Reproductive Health Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Vasectomy; Vasectomy reversal; Medicine; Prostate cancer; Vasovasostomy; Gynecology; Population; Cohort; Demography; Incidence (geometry); Meta-analysis; Cohort study; Obstetrics; Family planning; Cancer; Environmental health; Internal medicine; Research methodology","score_opus":0.49832401299518186,"score_gpt":0.5777435527172982,"score_spread":0.0794195397221163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890312272","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77644825,0.0009012372,0.0864347,0.054573007,0.04161349,0.01054446,0.015791425,0.00034144317,0.013351974],"genre_scores_gemma":[0.9845341,0.00007566468,0.00756731,0.00060386956,0.0037656135,0.000073805844,0.0027877924,0.00002873153,0.000563125],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99281204,0.0004586238,0.0018304706,0.0012392739,0.0031076444,0.0005519581],"domain_scores_gemma":[0.98987854,0.0011336865,0.0023417475,0.002210034,0.0042867684,0.00014924348],"candidate_categories":["sts","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.012692622,0.00029030172,0.00074016163,0.0009925811,0.002368452,0.00028439873,0.0074987956,0.00007732404,0.0009783312],"category_scores_gemma":[0.003871776,0.00018598871,0.00019724268,0.0016169029,0.00043771448,0.003512289,0.0031198538,0.0005548455,0.0000146186785],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009861564,0.0004504571,0.91040355,0.000023748114,0.056833524,0.0000080559685,0.0033783081,0.0047223037,0.00007789326,0.0041192165,0.015528488,0.0034683181],"study_design_scores_gemma":[0.0012674701,0.0001843995,0.7791499,0.0000637888,0.013667331,0.000018032406,0.0030871658,0.17108724,0.0000049885784,0.00076683395,0.030400489,0.00030236205],"about_ca_topic_score_codex":0.0035609407,"about_ca_topic_score_gemma":0.0051145665,"teacher_disagreement_score":0.20808583,"about_ca_system_score_codex":0.00049418275,"about_ca_system_score_gemma":0.00041294162,"threshold_uncertainty_score":0.9999349},"labels":[],"label_agreement":null},{"id":"W2890353242","doi":"10.23889/ijpds.v3i4.969","title":"Developing and implementing linked electronic medical record and administrative data in primary care practice for diabetes in Alberta","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Diabetes Management and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; Alberta Innovates; University of Calgary; University of Alberta","funders":"","keywords":"Medicine; Medical record; Dashboard; Family medicine; Diabetes mellitus; Primary care; Health care; Medical emergency; Database; Internal medicine","score_opus":0.09774433257932558,"score_gpt":0.4586427995717345,"score_spread":0.3608984669924089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890353242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9863506,0.00007428665,0.0019048738,0.010286949,0.00061488897,0.0004530678,0.00005036605,0.000004773684,0.00026018228],"genre_scores_gemma":[0.9777773,0.0001053665,0.019101532,0.00069686596,0.00039609458,0.000012628353,0.0018691273,0.000006058388,0.00003500302],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986061,0.000020608364,0.00034854063,0.00034422646,0.00042164605,0.0002589049],"domain_scores_gemma":[0.998846,0.00035035933,0.0001960762,0.00020268753,0.000333211,0.00007165122],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023810915,0.00006854794,0.000104631086,0.0002742014,0.00014589484,0.00018789516,0.00057196064,0.00002812741,0.000009099467],"category_scores_gemma":[0.0047925604,0.00006396002,0.0000072048006,0.00018745499,0.00009210631,0.0024468594,0.0004446492,0.00010962496,4.5058601e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001697968,0.00006960455,0.8406017,0.00008291382,0.000043423333,0.0000015830523,0.0006778077,3.7898886e-7,0.00017915174,0.0048001013,0.0003283982,0.15304519],"study_design_scores_gemma":[0.003064334,0.00045678703,0.87293357,0.00076443126,0.00006971185,0.000046818113,0.0018822944,0.048690893,0.000101470534,0.0023661966,0.069387585,0.00023592656],"about_ca_topic_score_codex":0.00021742188,"about_ca_topic_score_gemma":0.0033459365,"teacher_disagreement_score":0.15280926,"about_ca_system_score_codex":0.00027500567,"about_ca_system_score_gemma":0.0006557661,"threshold_uncertainty_score":0.5737489},"labels":[],"label_agreement":null},{"id":"W2890386437","doi":"10.23889/ijpds.v3i4.913","title":"Access to palliative care in Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Palliative Care and End-of-Life Issues","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Palliative care; Medicine; Health care; Emergency department; End-of-life care; Intensive care; Acute care; Family medicine; Medical emergency; Nursing; Gerontology; Intensive care medicine","score_opus":0.30866071048735877,"score_gpt":0.5490978795579466,"score_spread":0.24043716907058788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890386437","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99179965,0.0001013286,0.00303338,0.0019818111,0.002048847,0.00019797753,0.00034511977,0.0000039419797,0.000487917],"genre_scores_gemma":[0.99258244,0.000038863196,0.0061054667,0.0007038914,0.00037720808,0.0000028995532,0.00015811586,0.0000040406658,0.000027055043],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998663,0.000008940151,0.0002760751,0.00019758045,0.00071411266,0.00014025495],"domain_scores_gemma":[0.9982366,0.000058735364,0.00013300676,0.00019151426,0.001263361,0.00011678167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026623608,0.00005790951,0.00011044512,0.0002575257,0.00007445143,0.000064727596,0.0010042621,0.000012783495,0.000045704488],"category_scores_gemma":[0.0012182095,0.000049198443,0.000016784297,0.00033481064,0.00005884353,0.0008159369,0.0002141835,0.000066742476,0.0000025316774],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016356714,0.000012218238,0.9805794,0.0000074409177,0.000014333404,0.00000972113,0.0008141679,0.00010985416,0.0003228165,0.00022888712,0.0021692165,0.015568388],"study_design_scores_gemma":[0.00067888014,0.00011174034,0.9492783,0.0004783461,0.000009526048,0.000009981569,0.0012254033,0.0033055379,0.003048564,0.00020682687,0.041559104,0.00008781581],"about_ca_topic_score_codex":0.29875618,"about_ca_topic_score_gemma":0.67398757,"teacher_disagreement_score":0.3752314,"about_ca_system_score_codex":0.0008092555,"about_ca_system_score_gemma":0.0013815545,"threshold_uncertainty_score":0.7059134},"labels":[],"label_agreement":null},{"id":"W2890396880","doi":"10.23889/ijpds.v3i4.854","title":"Diabetic Ketoacidosis (DKA) at Diabetes Diagnosis in Children (0-18 years) in Ontario, Canada: A Population-Based Retrospective Cohort Study of Health Administrative Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Diabetes and associated disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Laurentian University","funders":"","keywords":"Diabetic ketoacidosis; Medicine; Pediatrics; Diabetes mellitus; Population; Retrospective cohort study; Odds ratio; Type 1 diabetes; Cohort; Surgery; Internal medicine; Environmental health; Endocrinology","score_opus":0.03612433319357378,"score_gpt":0.3389424740710619,"score_spread":0.30281814087748815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890396880","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99779457,0.000038899856,0.000022918992,0.00018769548,0.00040111062,0.0004891345,0.0010490393,0.0000022733775,0.000014364643],"genre_scores_gemma":[0.99496984,0.00000917425,0.00023821215,0.00013836028,0.00007086067,0.000022345272,0.0045248093,0.000009089015,0.000017328864],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99788696,0.00007903928,0.00054033974,0.0005518413,0.00067324645,0.00026858738],"domain_scores_gemma":[0.99864745,0.000037220503,0.00046772885,0.00051423226,0.00026016435,0.00007319081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013739105,0.00011500629,0.00021182936,0.00019167559,0.00015012338,0.00007051019,0.0013770817,0.00004043414,0.000048177157],"category_scores_gemma":[0.00074968906,0.0001195643,0.000022569187,0.00027266485,0.0000780408,0.00009799562,0.0004234071,0.00010333574,3.2673597e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023166567,0.00022755415,0.9979055,0.0000011244332,0.000053344073,4.176988e-7,0.000038716655,0.00020642034,0.000085458734,0.000005648972,0.0008157181,0.0006369182],"study_design_scores_gemma":[0.000883304,0.00027476755,0.9967282,0.00003614298,0.000010821308,6.548108e-7,0.00006155219,0.0015890268,0.00013345812,0.000040994357,0.000121931465,0.000119179334],"about_ca_topic_score_codex":0.685987,"about_ca_topic_score_gemma":0.9745987,"teacher_disagreement_score":0.28861174,"about_ca_system_score_codex":0.000894462,"about_ca_system_score_gemma":0.001102004,"threshold_uncertainty_score":0.48756906},"labels":[],"label_agreement":null},{"id":"W2890397054","doi":"10.23889/ijpds.v3i4.950","title":"Impact of a web-based clinical decision-support system on pulmonary embolism diagnoses","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Clinical decision support system; Medical diagnosis; Medicine; Medical record; Diagnosis code; Medical emergency; Decision support system; MEDLINE; Intervention (counseling); Intensive care medicine; Computer science; Internal medicine; Data mining; Nursing","score_opus":0.08323444961744575,"score_gpt":0.4675881490310234,"score_spread":0.38435369941357767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890397054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98603725,0.000016998114,0.0066252626,0.0005412809,0.004652989,0.00043514403,0.00037345078,0.00003481984,0.0012827779],"genre_scores_gemma":[0.99281126,0.00006133981,0.005190886,0.0003985301,0.0012665115,0.000009080161,0.00021473241,0.000013445872,0.000034222023],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99718386,0.000032597483,0.0008289443,0.00041295536,0.0013080093,0.00023366342],"domain_scores_gemma":[0.9972,0.00031223867,0.0005085436,0.00061293173,0.0011342156,0.00023204328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022148038,0.00012922156,0.00033319285,0.0005316227,0.00022382631,0.0001281544,0.0011861265,0.000051510648,0.00018131966],"category_scores_gemma":[0.0016690464,0.00009428846,0.00020323307,0.00027940507,0.00026039436,0.0007064156,0.0002332714,0.00012656045,0.000040411396],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001990383,0.003165055,0.58308196,0.000058426787,0.00044223596,0.00016003595,0.000063806074,0.00085121515,0.0007703714,0.010588011,0.05796794,0.34086055],"study_design_scores_gemma":[0.0015018128,0.0012495157,0.93954575,0.00043506554,0.000075994685,0.0001306447,0.000028719378,0.049885187,0.000064811524,0.00018300847,0.0067971135,0.00010236855],"about_ca_topic_score_codex":0.00010303056,"about_ca_topic_score_gemma":0.00001288169,"teacher_disagreement_score":0.3564638,"about_ca_system_score_codex":0.00027036428,"about_ca_system_score_gemma":0.00058590015,"threshold_uncertainty_score":0.38449717},"labels":[],"label_agreement":null},{"id":"W2890423698","doi":"10.23889/ijpds.v3i4.660","title":"Using administrative data to examine government service transitions of children, youth and young adults in Alberta, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Income Support; Government (linguistics); Harm; Service (business); Service delivery framework; Mental health; Business; Psychology; Medicine; Political science; Psychiatry; Social psychology; Marketing","score_opus":0.215893078539556,"score_gpt":0.3777235805440734,"score_spread":0.1618305020045174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890423698","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9736362,0.000018355851,0.0078620855,0.005576098,0.000861449,0.00024022874,0.0115979705,0.0000016075699,0.00020598661],"genre_scores_gemma":[0.9955495,0.000011493228,0.0033821526,0.00052657985,0.00014371262,0.0000015013139,0.0003632079,0.000003864282,0.000017991926],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989082,0.0000076094793,0.00045994652,0.00030716846,0.00017707815,0.00013996003],"domain_scores_gemma":[0.9992103,0.000022397378,0.00024499782,0.0003108733,0.00011971605,0.000091700545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000741883,0.000058983464,0.000103566934,0.00013361676,0.0001248343,0.000072391485,0.0009395798,0.000014284006,0.000014378569],"category_scores_gemma":[0.0003384622,0.00006588361,0.0000067169326,0.00022780098,0.00003848276,0.0010030943,0.0002685477,0.000048551054,0.0000010719892],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000617839,0.00048774816,0.7516433,0.00009485657,0.00025755077,0.0000091477705,0.015891548,0.0017637206,0.0002197937,0.20994896,0.0019150868,0.017150465],"study_design_scores_gemma":[0.0007575732,0.000092281494,0.88536483,0.00012349103,0.000008395458,0.00003109533,0.000672759,0.108331025,0.000040993364,0.0008385543,0.00355363,0.00018537928],"about_ca_topic_score_codex":0.79195225,"about_ca_topic_score_gemma":0.87208486,"teacher_disagreement_score":0.2091104,"about_ca_system_score_codex":0.00024830457,"about_ca_system_score_gemma":0.00015950798,"threshold_uncertainty_score":0.26866555},"labels":[],"label_agreement":null},{"id":"W2890431044","doi":"10.23889/ijpds.v3i4.634","title":"Use of Large Data Sets in Evaluating Program Outcome in Pediatric Hearing Loss","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Noise Effects and Management","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; University of Ottawa; McGill University; Children's Hospital of Eastern Ontario; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Hearing loss; Relative risk; Poisson regression; Breastfeeding; Propensity score matching; Pregnancy; Pediatrics; Gestational age; Birth weight; Demography; Environmental health; Population; Confidence interval; Audiology","score_opus":0.5224951171454437,"score_gpt":0.6357025829192591,"score_spread":0.11320746577381535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890431044","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99316233,0.000014999419,0.0020105373,0.0006568509,0.002952494,0.000830441,0.00029533549,0.0000141430255,0.000062879575],"genre_scores_gemma":[0.9805885,0.000019937246,0.018265812,0.00018673568,0.00047363795,0.00001725315,0.00038107426,0.000007636184,0.000059397076],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975352,0.00013656901,0.0008239388,0.00035375796,0.0008153698,0.0003351465],"domain_scores_gemma":[0.99816716,0.0002857627,0.00047711248,0.0005752355,0.00042998488,0.00006476049],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008007204,0.00007457801,0.00013275552,0.00059539545,0.00030957113,0.00008855178,0.0018120653,0.000035547906,0.00004700021],"category_scores_gemma":[0.0037877273,0.000064274966,0.00001818196,0.0004917699,0.00005275502,0.0031128544,0.0017282268,0.00024892288,0.000010148301],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004481534,0.00009845675,0.98133963,0.00003370585,0.0000048889533,0.0000036787421,0.00018069279,0.00013469442,0.000047254798,0.0011687818,0.00069758354,0.01624579],"study_design_scores_gemma":[0.0007317553,0.000058698068,0.8391259,0.00012542357,0.000008506303,0.0000024343424,0.000071807466,0.15616049,0.0000018403673,0.00037641288,0.0032705518,0.00006618288],"about_ca_topic_score_codex":0.00077914854,"about_ca_topic_score_gemma":0.0020708356,"teacher_disagreement_score":0.1560258,"about_ca_system_score_codex":0.00020052338,"about_ca_system_score_gemma":0.00021409715,"threshold_uncertainty_score":0.4534537},"labels":[],"label_agreement":null},{"id":"W2890434503","doi":"10.23889/ijpds.v3i4.771","title":"Diagnosis incidence of autism spectrum disorders is underestimated in Australian children, and there are inequalities in access to diagnosis and treatment services: a data linkage study of health service usage","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Incidence (geometry); Guideline; Population; Breast cancer; Family medicine; Cohort; Health care; Pediatrics; Demography; Cancer; Environmental health; Internal medicine","score_opus":0.20348680767543958,"score_gpt":0.46950297908423055,"score_spread":0.26601617140879097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890434503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.983566,0.00011926212,0.000052813026,0.014215506,0.00011716718,0.0008926548,0.0010242017,0.0000066369716,0.0000057506345],"genre_scores_gemma":[0.9983164,0.00067254,0.0003098426,0.00028965092,0.00003287137,0.000023651133,0.00034255622,0.0000069782336,0.0000055046103],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99822986,0.000053135336,0.00057460763,0.000434028,0.0005290257,0.0001793354],"domain_scores_gemma":[0.9988258,0.00009109003,0.00040820724,0.0004972872,0.00007932915,0.00009831923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008244193,0.00012005255,0.00024943633,0.0005214624,0.000095579744,0.00018503616,0.00110233,0.000020581621,0.000033199212],"category_scores_gemma":[0.0001220956,0.00010337225,0.000010214761,0.00054617133,0.00010731855,0.0019251915,0.0008610378,0.000062189756,3.6179364e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000073886964,0.00047753524,0.99260014,0.00009000564,0.00004502039,0.0000036501228,0.001644644,0.0001266939,0.0000025898682,0.00014691372,0.00007289046,0.0047160285],"study_design_scores_gemma":[0.001656441,0.00039956172,0.98787946,0.00091889634,0.000030607305,0.000006276553,0.002192776,0.005894489,0.000010236758,0.0008880411,0.00004328322,0.00007995497],"about_ca_topic_score_codex":0.03866236,"about_ca_topic_score_gemma":0.10717066,"teacher_disagreement_score":0.0685083,"about_ca_system_score_codex":0.00019329556,"about_ca_system_score_gemma":0.00015682584,"threshold_uncertainty_score":0.9677393},"labels":[],"label_agreement":null},{"id":"W2890461750","doi":"10.23889/ijpds.v3i4.1038","title":"UK and Canadian Gulf War Veteran Mortality: Using A Fellow Military Cohort as a Comparison Population","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Veterans Affairs Canada","funders":"","keywords":"Comparability; Cohort; Christian ministry; Population; Demography; Record linkage; Medicine; Linkage (software); Actuarial science; Environmental health; Political science; Business; Law; Sociology","score_opus":0.08258738455494784,"score_gpt":0.4014337921117435,"score_spread":0.31884640755679566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890461750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9905556,0.00003084071,0.006851142,0.0004839173,0.0011360958,0.00038095526,0.00018712446,0.000012387799,0.00036192895],"genre_scores_gemma":[0.9908602,0.00003468175,0.0076139797,0.0007753317,0.00033232718,0.000004699423,0.00033395932,0.000013395443,0.000031385855],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972064,0.00006771244,0.0005036299,0.0006919569,0.0011044823,0.00042581043],"domain_scores_gemma":[0.99876714,0.00005213476,0.00022390844,0.00042305727,0.000087050765,0.00044671507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002273357,0.00014949292,0.00014937668,0.00026195406,0.001053488,0.00016716497,0.0009801093,0.00005528736,0.0005257367],"category_scores_gemma":[0.0005888299,0.00015210641,0.000030803898,0.00026091887,0.0004410838,0.0024899754,0.0003786926,0.00017266517,0.00005709422],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017371982,0.000018760362,0.9867644,0.0000017484248,0.000014539678,0.000006493309,0.00024911275,0.0010326131,0.0011608381,0.000055751072,0.0002597366,0.010418654],"study_design_scores_gemma":[0.00022955133,0.000048366746,0.8033254,0.000032224772,0.000021637296,0.000106232605,0.00008940361,0.19176446,0.00006119103,0.0011708641,0.0029939495,0.00015668423],"about_ca_topic_score_codex":0.27307722,"about_ca_topic_score_gemma":0.11299314,"teacher_disagreement_score":0.19073184,"about_ca_system_score_codex":0.0011174532,"about_ca_system_score_gemma":0.000119515425,"threshold_uncertainty_score":0.9031924},"labels":[],"label_agreement":null},{"id":"W2890465937","doi":"10.23889/ijpds.v3i4.928","title":"25-hydroxyvitamin D and health service utilization for asthma in early childhood","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child and Adolescent Health","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"Medicine; Asthma; Vitamin D and neurology; Emergency department; Pediatrics; Logistic regression; vitamin D deficiency; Population; Poisson regression; Prospective cohort study; Cohort; Pregnancy; Internal medicine; Environmental health; Psychiatry","score_opus":0.18685189534663313,"score_gpt":0.5074012556314998,"score_spread":0.3205493602848667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890465937","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9495691,0.00008742202,0.022688463,0.02083486,0.0046037086,0.0013775908,0.0007091489,0.00003444299,0.00009523834],"genre_scores_gemma":[0.9890548,0.000079407626,0.0041045784,0.004645371,0.0015611628,0.0000058913156,0.00045349356,0.000012729578,0.000082544495],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99800104,0.00007329851,0.0006607513,0.00038345307,0.0004799706,0.00040150585],"domain_scores_gemma":[0.9982641,0.00012099353,0.00046479318,0.00024532815,0.00071297,0.0001918396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032916493,0.00009828604,0.00014427444,0.00036852926,0.0012722599,0.00010075095,0.0008080757,0.000053196978,0.000025826213],"category_scores_gemma":[0.0005579709,0.00008925906,0.000018796147,0.0003577621,0.00007083057,0.0016169184,0.00024190321,0.0002269373,0.000010341369],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001584113,0.00033482714,0.77478987,0.0001968072,0.00002432822,0.0000013765522,0.012977466,0.00005067821,0.00019448846,0.043013483,0.00976615,0.15849215],"study_design_scores_gemma":[0.0014215787,0.00011063076,0.95932305,0.00038096463,0.0000018060168,0.00001157649,0.00039136547,0.018343538,0.0000046675377,0.0027762265,0.017145686,0.000088896115],"about_ca_topic_score_codex":0.00069651613,"about_ca_topic_score_gemma":0.0026722034,"teacher_disagreement_score":0.18453322,"about_ca_system_score_codex":0.0002952806,"about_ca_system_score_gemma":0.00071738334,"threshold_uncertainty_score":0.9785323},"labels":[],"label_agreement":null},{"id":"W2890467998","doi":"10.23889/ijpds.v3i4.825","title":"Establishing the Occupational Disease Surveillance System (ODSS) for Ontario: a linkage of administrative data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Occupational Cancer Research Centre; Cancer Care Ontario","funders":"","keywords":"Medicine; Population; Disease; Record linkage; Environmental health; Health care; Medical emergency","score_opus":0.4542605606058225,"score_gpt":0.6035969769704277,"score_spread":0.1493364163646052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890467998","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5096857,0.0002473507,0.32497537,0.023445327,0.040654317,0.010427104,0.08702164,0.00013305368,0.0034101496],"genre_scores_gemma":[0.98351216,0.000008735117,0.0081151845,0.00026587048,0.0024036334,0.00008510612,0.005244351,0.000011874935,0.00035308904],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9962398,0.00021829273,0.0009770484,0.0005168912,0.0016033824,0.0004445864],"domain_scores_gemma":[0.9905477,0.003263344,0.0008581364,0.0010614226,0.0039716284,0.000297764],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.008840293,0.000119609256,0.00017628663,0.00022385753,0.002542564,0.00016377735,0.004453733,0.000057907662,0.000119123506],"category_scores_gemma":[0.0102198925,0.00008567584,0.00004683478,0.00033811355,0.00034367773,0.0027232538,0.00089383236,0.00035506662,0.000014432332],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031411406,0.000101996644,0.9181957,0.00019531908,0.00006930662,0.0000026284536,0.000795614,0.000092533934,0.000051366045,0.05397557,0.015195638,0.008183182],"study_design_scores_gemma":[0.00084039266,0.00010543044,0.864681,0.0002401984,0.000013999238,0.00000769291,0.00043680036,0.08204329,0.000003434773,0.001051787,0.050470695,0.00010526071],"about_ca_topic_score_codex":0.0057975794,"about_ca_topic_score_gemma":0.025755761,"teacher_disagreement_score":0.47382647,"about_ca_system_score_codex":0.00061031344,"about_ca_system_score_gemma":0.0064063016,"threshold_uncertainty_score":0.99922645},"labels":[],"label_agreement":null},{"id":"W2890489047","doi":"10.23889/ijpds.v3i4.624","title":"Using administrative health data to inform health service planning for specialist cancer care in Nova Scotia, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Medicine; Cancer; Cancer registry; Prostate cancer; Family medicine; Nova scotia; Population; Cohort; Health care; Demography; Internal medicine; Environmental health; Geography","score_opus":0.6069313147067777,"score_gpt":0.5956575580756278,"score_spread":0.011273756631149934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890489047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7997878,0.0010444141,0.054406416,0.10388195,0.015446941,0.0031459786,0.021870734,0.000035086032,0.00038068468],"genre_scores_gemma":[0.9485243,0.0000072771595,0.035078917,0.012603162,0.0016978697,0.000003599542,0.002057841,0.000009877755,0.000017145736],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99754953,0.000014181586,0.00058934273,0.0004214253,0.0010445798,0.0003809296],"domain_scores_gemma":[0.99747455,0.000043400454,0.00040670778,0.00042964405,0.0013268025,0.00031892344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012857658,0.000110629924,0.0002077916,0.00024099786,0.00046802184,0.00019683504,0.0014995519,0.000022134078,0.000032871565],"category_scores_gemma":[0.0006196725,0.000105325766,0.000016019385,0.0005972518,0.000053844284,0.0017292937,0.00034890953,0.00013239046,0.0000010570254],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040821848,0.00011598615,0.67578703,0.00038910544,0.00016340498,0.00005873025,0.010058076,0.013575297,0.00051573187,0.0026352734,0.13159367,0.16102548],"study_design_scores_gemma":[0.003589168,0.0012299053,0.63558334,0.0041167187,0.000036565634,0.00050309533,0.0100892065,0.15537113,0.00018451331,0.0001665834,0.18855861,0.0005711797],"about_ca_topic_score_codex":0.7356947,"about_ca_topic_score_gemma":0.96770424,"teacher_disagreement_score":0.23200952,"about_ca_system_score_codex":0.0026199052,"about_ca_system_score_gemma":0.010786218,"threshold_uncertainty_score":0.9948217},"labels":[],"label_agreement":null},{"id":"W2890490695","doi":"10.23889/ijpds.v3i4.924","title":"How integration of the federal Indian Register has enhanced First Nations-specific analysis of ICES data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Laurentian University; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Residence; Population; Geography; Indigenous; Linkage (software); Economic growth; Demography; Economics; Sociology; Ecology","score_opus":0.31988031473532624,"score_gpt":0.5346304180616988,"score_spread":0.2147501033263725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890490695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.810831,0.000070772665,0.081951074,0.08149655,0.018949855,0.0011744064,0.0040175146,0.000027253713,0.0014815609],"genre_scores_gemma":[0.99358886,0.0000703146,0.0027620564,0.00037622766,0.0011780824,0.000012357951,0.0014772553,0.000006862662,0.0005279878],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99741846,0.00013375746,0.00085055275,0.00034505533,0.0009781814,0.00027397613],"domain_scores_gemma":[0.99430853,0.00049218006,0.0015621309,0.001179442,0.0023539143,0.00010377739],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0029354717,0.000093832525,0.00019286912,0.0009408857,0.0024319806,0.0002527211,0.0035564115,0.00007200963,0.00011729571],"category_scores_gemma":[0.004413563,0.0000660057,0.00006104172,0.0017593132,0.0004383924,0.0032554967,0.00064379786,0.0002137708,0.0000033326544],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006417986,0.0008044896,0.46526214,0.0003704997,0.0014598877,8.06568e-7,0.05337574,0.00074493425,0.014422655,0.13611975,0.2444739,0.082323395],"study_design_scores_gemma":[0.00070069666,0.00007841859,0.7107826,0.00040479007,0.00011704736,0.000005209842,0.005105002,0.037974935,0.00047040454,0.0012031356,0.24297519,0.00018257028],"about_ca_topic_score_codex":0.0019683084,"about_ca_topic_score_gemma":0.020077335,"teacher_disagreement_score":0.24552046,"about_ca_system_score_codex":0.00027840893,"about_ca_system_score_gemma":0.00090297806,"threshold_uncertainty_score":0.99886674},"labels":[],"label_agreement":null},{"id":"W2890540419","doi":"10.23889/ijpds.v3i4.806","title":"Trends in Socioeconomic Inequalities in Ischemic Heart Disease, 2000-2012","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Public Health Policies and Epidemiology","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Institute for Work & Health; Public Health Ontario; University of Toronto","funders":"","keywords":"Socioeconomic status; Poisson regression; Inequality; Medicine; Demography; Ethnic group; Relative risk; Household income; Confidence interval; Geography; Environmental health; Population; Internal medicine; Mathematics","score_opus":0.10651278488340077,"score_gpt":0.41389826591224965,"score_spread":0.3073854810288489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890540419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9163933,0.000063534615,0.0003795544,0.07527969,0.0040755263,0.0001189393,0.00011713198,0.00002246986,0.0035498403],"genre_scores_gemma":[0.9837462,0.000007152389,0.00031680998,0.012959721,0.00250373,0.000005384169,0.00030728814,0.00000586389,0.00014787866],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99861443,0.000013279622,0.00051807467,0.00025558032,0.00024720456,0.0003514536],"domain_scores_gemma":[0.9992686,0.000052553,0.00023986727,0.00019618552,0.00020432657,0.000038477297],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023597588,0.00008055488,0.00012746178,0.000930877,0.00016905402,0.00030309558,0.0010431006,0.000030923522,0.00028174496],"category_scores_gemma":[0.0006472559,0.00007520517,0.00002850331,0.0003412175,0.00015141434,0.005890239,0.00032212544,0.000107500164,0.00006930583],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009734789,0.000057447138,0.5292407,0.000013577364,0.000005075418,0.0000020228617,0.000051061514,0.00091005064,0.00004026943,0.04814985,0.41184992,0.009582661],"study_design_scores_gemma":[0.00029217388,0.000004392587,0.44197986,0.000020183497,0.0000016494378,0.0000035976266,0.000054103675,0.05204874,2.9924792e-7,0.0064463164,0.49907282,0.00007584327],"about_ca_topic_score_codex":0.006334564,"about_ca_topic_score_gemma":0.0014744144,"teacher_disagreement_score":0.08726085,"about_ca_system_score_codex":0.000244751,"about_ca_system_score_gemma":0.0001192353,"threshold_uncertainty_score":0.95760083},"labels":[],"label_agreement":null},{"id":"W2890553281","doi":"10.23889/ijpds.v3i4.875","title":"Improving the Measurement of Health System Performance across the Rural-Urban Continuum","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of Toronto","funders":"","keywords":"Health care; Equity (law); Performance indicator; Context (archaeology); Population health; Geography; Suite; Health indicator; Population; Environmental health; Business; Medicine; Marketing; Economic growth; Political science","score_opus":0.15819619285823258,"score_gpt":0.48657544816245546,"score_spread":0.32837925530422285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890553281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88749874,0.0005422907,0.020829245,0.052852556,0.033793926,0.002311223,0.0007419001,0.00008096061,0.001349188],"genre_scores_gemma":[0.9945532,0.00003616623,0.00046647235,0.0033284053,0.0014101722,0.000019721918,0.00003764753,0.000007657911,0.00014053483],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968063,0.00017787784,0.0009710335,0.00019549736,0.0014020402,0.0004472154],"domain_scores_gemma":[0.9956709,0.0002205171,0.001271658,0.00057766173,0.0021773432,0.000081875834],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.015085995,0.00008931288,0.00016508454,0.000081459184,0.0042077485,0.00009507489,0.0025478092,0.00003333123,0.000022624254],"category_scores_gemma":[0.0007977382,0.000047426183,0.000042977044,0.00022836587,0.00028058997,0.0011317611,0.00055597787,0.00030015054,0.000016041437],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005364677,0.000074533506,0.521929,0.00054660614,0.000120437064,9.618378e-7,0.012797347,0.000037548547,0.002041276,0.015852122,0.18257226,0.26349142],"study_design_scores_gemma":[0.0013266902,0.0002300307,0.8063109,0.00067824865,0.000019648203,0.000040147344,0.008918476,0.019085122,0.00017012909,0.00022603464,0.16281535,0.00017923024],"about_ca_topic_score_codex":0.0011893712,"about_ca_topic_score_gemma":0.00082693447,"teacher_disagreement_score":0.28438187,"about_ca_system_score_codex":0.0011005673,"about_ca_system_score_gemma":0.001771698,"threshold_uncertainty_score":0.9970886},"labels":[],"label_agreement":null},{"id":"W2890564363","doi":"10.23889/ijpds.v3i4.720","title":"Social Class and Hospitalization in Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Census; Operationalization; Social class; Record linkage; Demography; Population; Health care; Medicine; Geography; Environmental health; Economic growth; Sociology; Political science","score_opus":0.07406183465839908,"score_gpt":0.44655751708689057,"score_spread":0.3724956824284915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890564363","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9611199,0.000030073536,0.0012603209,0.030620748,0.0051618703,0.00017970295,0.000109748056,0.0000094496945,0.0015081731],"genre_scores_gemma":[0.99742144,0.000041024377,0.00040995638,0.001119029,0.0008890689,0.0000015144427,0.000034286826,0.0000025275294,0.00008115805],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99871546,0.000029914767,0.00021486466,0.00015255551,0.0006703876,0.00021681427],"domain_scores_gemma":[0.99930954,0.000059473805,0.0001127637,0.000066950604,0.0003544664,0.00009682101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012393229,0.000038115784,0.00005624592,0.00011065842,0.0008858382,0.0002574004,0.0006899794,0.000019629088,0.000037165137],"category_scores_gemma":[0.0009173084,0.00003749935,0.000007645921,0.00020069406,0.00019462622,0.0015047024,0.00009744439,0.000053361695,8.483284e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016649288,0.00000944361,0.8237595,0.0000037203836,0.0000037650168,0.0000021477908,0.0013768701,0.00001082894,0.000003881125,0.14680617,0.007180372,0.02082668],"study_design_scores_gemma":[0.00020624833,0.000007302264,0.89081055,0.000016985881,0.0000016167606,0.0000030886463,0.0012617703,0.0049319523,0.0000026769303,0.003576762,0.09911354,0.000067489156],"about_ca_topic_score_codex":0.8398902,"about_ca_topic_score_gemma":0.97218037,"teacher_disagreement_score":0.14322941,"about_ca_system_score_codex":0.00072604016,"about_ca_system_score_gemma":0.0018750404,"threshold_uncertainty_score":0.68132406},"labels":[],"label_agreement":null},{"id":"W2890569682","doi":"10.23889/ijpds.v3i4.792","title":"Linking Pan-Canadian Administrative and Clinical Registry Data to gain insights across the continuum of care","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Dialysis; Medicine; Health care; Intensive care medicine; Emergency medicine; Modalities; Medical emergency; Internal medicine","score_opus":0.3543951741404314,"score_gpt":0.6119679175879891,"score_spread":0.25757274344755765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890569682","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.936635,0.00031782454,0.0038629205,0.033953503,0.014619139,0.0012658377,0.0068887225,0.000022855682,0.0024341904],"genre_scores_gemma":[0.98810756,0.00007161024,0.0031077398,0.0060406155,0.0017729497,0.000004744803,0.00070597243,0.0000069079547,0.00018190574],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977871,0.00015014436,0.00080619944,0.00038583824,0.00053856336,0.00033213408],"domain_scores_gemma":[0.9962171,0.0006718834,0.00053133006,0.00085901713,0.0014319774,0.00028873992],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003465608,0.000083812345,0.00016958815,0.00012832295,0.0018092274,0.00012106816,0.0031015135,0.00007988771,0.000029346063],"category_scores_gemma":[0.0033524751,0.000058372174,0.000024828398,0.00020100674,0.00037974233,0.0012284911,0.0011393438,0.00037441842,0.000012174544],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030280827,0.00003149199,0.8407917,0.000054531083,0.00005900089,0.000009964432,0.008053743,0.0000013789082,0.00010520943,0.005867132,0.06435111,0.08037194],"study_design_scores_gemma":[0.00050714443,0.00016512237,0.6663614,0.00018782026,0.000014600757,0.000015837662,0.004076353,0.0007035607,0.000012132922,0.00084330287,0.3270105,0.00010220026],"about_ca_topic_score_codex":0.0069221626,"about_ca_topic_score_gemma":0.29430273,"teacher_disagreement_score":0.28738058,"about_ca_system_score_codex":0.00028223466,"about_ca_system_score_gemma":0.0030752916,"threshold_uncertainty_score":0.99969083},"labels":[],"label_agreement":null},{"id":"W2890574840","doi":"10.23889/ijpds.v3i4.981","title":"Prenatal care of women who give birth to Children with Fetal Alcohol Spectrum Disorder in a universal health care system: A retrospective cohort study utilizing linkable administrative data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Prenatal Substance Exposure Effects","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Medicine; Fetal Alcohol Spectrum Disorder; Population; Prenatal care; Pregnancy; Retrospective cohort study; Family medicine; Health care; Outreach; Pediatrics; Cohort; Environmental health","score_opus":0.031584391061254935,"score_gpt":0.36650869351711995,"score_spread":0.334924302455865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890574840","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922681,0.00011353476,0.0018249019,0.00019194072,0.0005345137,0.0023237304,0.0026317802,0.000027022006,0.0000845109],"genre_scores_gemma":[0.995986,0.0000045403785,0.002326803,0.000037926926,0.00030903445,0.00002396998,0.0012756848,0.000019547955,0.00001647843],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9965672,0.00008220369,0.00052529934,0.00084251567,0.001525791,0.00045699684],"domain_scores_gemma":[0.9973528,0.000047661008,0.00047570257,0.0008921545,0.00093392207,0.00029779397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013937647,0.00019450198,0.0004235547,0.00054913945,0.00028691467,0.00013763492,0.0017856372,0.00003784061,0.000014033496],"category_scores_gemma":[0.0005903241,0.00016244505,0.000026917913,0.0007926896,0.00021134298,0.0020498198,0.00069048966,0.0002508472,0.0000023768273],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009723305,0.00013259926,0.9891219,0.000043111486,0.0001645507,0.000026842197,0.008291564,0.00006092998,0.000026150057,0.00028637005,0.000036636226,0.00083698035],"study_design_scores_gemma":[0.0027527858,0.0027007775,0.9707489,0.00068246416,0.00003196164,0.00018137123,0.020258201,0.0022872444,0.00014241168,0.000008454939,0.000046350488,0.00015908346],"about_ca_topic_score_codex":0.0019466159,"about_ca_topic_score_gemma":0.006387276,"teacher_disagreement_score":0.018373042,"about_ca_system_score_codex":0.0031036923,"about_ca_system_score_gemma":0.0011580812,"threshold_uncertainty_score":0.8116048},"labels":[],"label_agreement":null},{"id":"W2890579496","doi":"10.23889/ijpds.v3i4.951","title":"Inferring sensitivity and specificity of phenotyping algorithms using positive and negative predictive value in validation study in observational health data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Observational study; Sensitivity (control systems); Computer science; Data mining; Algorithm; Machine learning; Sample size determination; Population; Statistics; Medicine; Mathematics; Engineering","score_opus":0.19455924886969844,"score_gpt":0.4261974346695372,"score_spread":0.23163818579983875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890579496","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9394549,0.000008813537,0.058985684,0.00031335026,0.00023198024,0.0005569042,0.00041889556,0.000004021525,0.000025453399],"genre_scores_gemma":[0.97871137,0.000026002317,0.020899642,0.000102882754,0.00010578795,0.000002259036,0.0001439937,0.000006879888,0.0000012015846],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974505,0.0002782829,0.0005580736,0.00069200847,0.0007891132,0.00023204913],"domain_scores_gemma":[0.9987101,0.00034428365,0.00045389807,0.00029771467,0.00009516077,0.00009885359],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064020227,0.000111170426,0.0001684134,0.000260079,0.0003224945,0.0001067404,0.0005128829,0.000026919837,0.000013590885],"category_scores_gemma":[0.0013717444,0.00011680959,0.000007942086,0.0003844349,0.00042088432,0.0045228177,0.0012043265,0.00018122965,7.567091e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006741506,0.00013318981,0.96561027,0.0000035992268,0.0000098098635,0.0000036073163,0.0018548851,0.0070779473,0.0016415189,0.0001277892,0.0000031394945,0.023466842],"study_design_scores_gemma":[0.00036798362,0.000055846365,0.58658856,0.00006625459,0.0000032988048,0.000014993995,0.00045994352,0.41168925,0.00012212397,0.00056734635,0.000005487533,0.000058918176],"about_ca_topic_score_codex":0.009112163,"about_ca_topic_score_gemma":0.002768692,"teacher_disagreement_score":0.4046113,"about_ca_system_score_codex":0.0007086581,"about_ca_system_score_gemma":0.00011760956,"threshold_uncertainty_score":0.99748623},"labels":[],"label_agreement":null},{"id":"W2890597821","doi":"10.23889/ijpds.v3i4.1030","title":"Linking Clinical and Administrative Data to Inform Performance Measures Regarding Access to Specialist Care for Patients with Rheumatoid Arthritis","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Rheumatoid Arthritis Research and Therapies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Medicine; Rheumatoid arthritis; Cohort; Referral; Internal medicine; Performance indicator; Rheumatology; Physical therapy; Emergency medicine; Family medicine","score_opus":0.18294352006399914,"score_gpt":0.4665833547918632,"score_spread":0.283639834727864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890597821","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9831119,0.00011609292,0.011760293,0.0015120284,0.0012017171,0.000979983,0.0011823482,0.000016475227,0.00011914223],"genre_scores_gemma":[0.97900903,0.0009160376,0.017975334,0.00031722843,0.00063973235,0.000016339858,0.0011009309,0.000011819937,0.000013554051],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976624,0.000016125414,0.0004868991,0.00045033172,0.0011160468,0.0002681788],"domain_scores_gemma":[0.9964735,0.00010569351,0.00017496476,0.00047719892,0.0024175844,0.0003510497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001328955,0.00011042945,0.00019515006,0.0002905996,0.0008115725,0.0009728577,0.0015697074,0.00002974628,0.000015499138],"category_scores_gemma":[0.0026730702,0.000086581014,0.000022943217,0.0002520641,0.00028109137,0.003901728,0.0007150348,0.00012760593,0.0000048019515],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015345229,0.00004247378,0.5432508,0.000010405823,0.000044903565,0.000001777016,0.00046325903,0.0000055647433,0.000019941135,0.00031188675,0.0015610576,0.45275342],"study_design_scores_gemma":[0.0038758707,0.0018145873,0.73824555,0.0013968501,0.0000045290262,0.00010673184,0.00028358295,0.0025601906,0.00016461243,0.000112799054,0.2512183,0.0002164183],"about_ca_topic_score_codex":0.000029341107,"about_ca_topic_score_gemma":0.00053243357,"teacher_disagreement_score":0.45253703,"about_ca_system_score_codex":0.00007910244,"about_ca_system_score_gemma":0.00036701406,"threshold_uncertainty_score":0.93812895},"labels":[],"label_agreement":null},{"id":"W2890613648","doi":"10.23889/ijpds.v3i4.703","title":"The Effect of Surgical Site Infection on Cost and Utilization Following Primary Knee Replacement in Nova Scotia 2005-2014","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Orthopedic Infections and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"","keywords":"Medicine; Nova scotia; Emergency medicine; Knee replacement; Joint replacement; Cohort; Indirect costs; Arthroplasty; Surgery; Internal medicine; Business","score_opus":0.04062782537304898,"score_gpt":0.3992840104735223,"score_spread":0.3586561851004733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890613648","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99569744,0.000035771896,0.0013275655,0.00032794575,0.0018010391,0.0004186753,0.000028308801,0.000007151645,0.00035608266],"genre_scores_gemma":[0.9990957,0.0000814881,0.00024038646,0.0000335832,0.00024294062,0.000004341664,0.00020799736,0.0000051653356,0.000088400346],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99876475,0.000040786224,0.00030878445,0.00020923464,0.00053792587,0.00013850238],"domain_scores_gemma":[0.99922025,0.00015819794,0.00017848024,0.00019716169,0.0001841984,0.00006172056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019706446,0.00007468587,0.000107174885,0.00027640373,0.00025656325,0.00009505486,0.000101339814,0.000028164568,0.000023289664],"category_scores_gemma":[0.00031989155,0.0000485392,0.000037524187,0.0001956902,0.00012032375,0.0006100986,0.000085750624,0.00008735385,0.000007106517],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005761682,0.00005307307,0.9643403,0.000005918312,0.000033372922,0.000005510684,0.000018769144,0.000029718807,0.00016395813,0.00016382213,0.00029104168,0.034318294],"study_design_scores_gemma":[0.0035025673,0.0011928515,0.9740377,0.0001929424,0.000049787093,0.00023354865,0.00000449126,0.008418943,0.0005236285,0.000054601718,0.011725519,0.0000634212],"about_ca_topic_score_codex":0.00032247967,"about_ca_topic_score_gemma":0.0004904897,"teacher_disagreement_score":0.034254875,"about_ca_system_score_codex":0.00022273792,"about_ca_system_score_gemma":0.00007367812,"threshold_uncertainty_score":0.19793712},"labels":[],"label_agreement":null},{"id":"W2890617612","doi":"10.23889/ijpds.v3i4.765","title":"Making Sense of a Hot Mess: Cleaning and Validating Messy Administrative Data to study Supportive Housing in Winnipeg, Manitoba","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Missing data; Medical record; Population; Data collection; Database; Geography; Computer science; Medicine; Statistics; Environmental health","score_opus":0.4253102651549672,"score_gpt":0.5743870164524415,"score_spread":0.14907675129747427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890617612","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915327,0.000013088028,0.004874066,0.00047769846,0.0020689885,0.0005497729,0.00036914315,0.000012603233,0.000101950616],"genre_scores_gemma":[0.9877302,0.0000038395033,0.011382571,0.00010698817,0.0005954253,0.0000050800345,0.00015299299,0.00001064787,0.000012225546],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997598,0.00016965694,0.00076631526,0.00047292357,0.0007073599,0.00028576716],"domain_scores_gemma":[0.99762934,0.00033625355,0.0006425938,0.00047656088,0.00082330545,0.000091931965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00399056,0.000105763334,0.00019209483,0.00047060236,0.0007536279,0.00013377894,0.0011410445,0.000036707104,0.00003373062],"category_scores_gemma":[0.0023518167,0.00009727871,0.000014108953,0.00046365254,0.000115011746,0.0018476695,0.0011071152,0.00022161246,0.00000274532],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010705128,0.0003043261,0.9021228,0.00004277902,0.00010444188,0.000064932996,0.03975338,0.00006261362,0.0035452144,0.0009381175,0.0021093658,0.049881537],"study_design_scores_gemma":[0.0013450364,0.00043845264,0.89906347,0.00068844017,0.000049580955,0.00006494089,0.08771413,0.008948633,0.0001676788,0.0006492063,0.0006514361,0.00021902383],"about_ca_topic_score_codex":0.00091420807,"about_ca_topic_score_gemma":0.0051643527,"teacher_disagreement_score":0.04966251,"about_ca_system_score_codex":0.00018314189,"about_ca_system_score_gemma":0.00034441522,"threshold_uncertainty_score":0.5796373},"labels":[],"label_agreement":null},{"id":"W2890617759","doi":"10.23889/ijpds.v3i4.945","title":"Development and validation of data quality rules in administrative health data using association rule mining","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Association rule learning; Data mining; Coding (social sciences); Data quality; Medicine; Computer science; Statistics; Mathematics; Operations management; Engineering","score_opus":0.807174435393419,"score_gpt":0.661392854821811,"score_spread":0.14578158057160806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890617759","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9599777,0.000030613992,0.03296404,0.0028005294,0.0019125079,0.0003904786,0.0017716404,0.000013923411,0.0001385538],"genre_scores_gemma":[0.8189091,0.00004525279,0.17316316,0.0004896919,0.0005814524,0.0000038289495,0.006760197,0.0000063638086,0.00004097363],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99645364,0.00024287394,0.0015294361,0.00037022604,0.0011053939,0.00029841773],"domain_scores_gemma":[0.9959214,0.0005353165,0.0019615293,0.00062105776,0.0008077302,0.00015299539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020633172,0.0000813619,0.0001906795,0.0003083029,0.0010350792,0.00008004743,0.0015598014,0.00007028939,0.000034939058],"category_scores_gemma":[0.0070801605,0.00007499472,0.00000664724,0.00023523494,0.00009139332,0.0046500266,0.0010935854,0.00023549539,0.0000048588868],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003392341,0.00016206487,0.8034119,0.0003929478,0.00006507834,0.0000011457325,0.01561307,0.000049069225,0.0003531989,0.006272113,0.0063788053,0.16696136],"study_design_scores_gemma":[0.0019239729,0.00009227766,0.65882885,0.0012925831,0.000015663583,0.000013869176,0.004820134,0.296625,0.00010482569,0.0012577882,0.034772247,0.00025279805],"about_ca_topic_score_codex":0.00074257556,"about_ca_topic_score_gemma":0.00093107665,"teacher_disagreement_score":0.29657593,"about_ca_system_score_codex":0.0006694241,"about_ca_system_score_gemma":0.002363943,"threshold_uncertainty_score":0.84761244},"labels":[],"label_agreement":null},{"id":"W2890622483","doi":"10.23889/ijpds.v3i4.835","title":"Establishing an International Data Linkage Repository Workgroup Toward a Benchmarking Repository","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Workgroup; Benchmarking; Computer science; Record linkage; Linkage (software); Data science; Metadata; Field (mathematics); Custodians; Information repository; Data mining; World Wide Web; Computer data storage; Business","score_opus":0.40029979659605125,"score_gpt":0.5237836597062985,"score_spread":0.12348386311024723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890622483","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21213359,0.000094578085,0.6520772,0.006568337,0.111201406,0.0007887345,0.0029834895,0.0002100583,0.0139426105],"genre_scores_gemma":[0.93607724,0.000028386688,0.051103868,0.0007719413,0.008440174,0.0000058363103,0.0025277762,0.000017091945,0.0010277134],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99095744,0.00023238335,0.0015212129,0.0016031269,0.005276224,0.0004095967],"domain_scores_gemma":[0.9920226,0.0006548192,0.0012474771,0.003403968,0.002354161,0.000317009],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.018585568,0.0001968708,0.00021867454,0.00094456674,0.0014170788,0.009656461,0.025263684,0.00007588558,0.00016974578],"category_scores_gemma":[0.010372453,0.00016883342,0.00006958714,0.0007760925,0.0004997102,0.034311652,0.0059788083,0.00029930755,0.00003891655],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000671382,0.00071513624,0.11449294,0.000014224281,0.00031509373,0.0002175942,0.0026757834,0.001054542,0.004411707,0.051840838,0.14513107,0.6784597],"study_design_scores_gemma":[0.0008178101,0.00018729623,0.10740252,0.00015087024,0.000043511263,0.00049676176,0.0013462601,0.39453432,0.00025584837,0.012615853,0.4816495,0.00049944996],"about_ca_topic_score_codex":0.0004699212,"about_ca_topic_score_gemma":0.00018893105,"teacher_disagreement_score":0.72394365,"about_ca_system_score_codex":0.00028123936,"about_ca_system_score_gemma":0.00031697963,"threshold_uncertainty_score":0.99988294},"labels":[],"label_agreement":null},{"id":"W2890629418","doi":"10.23889/ijpds.v3i4.872","title":"Leveraging best practices in data governance: An organization-wide data inventory and mapping project to support a five year data strategy","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"College of Physicians and Surgeons of Ontario","funders":"","keywords":"Data governance; Data quality; Data warehouse; Computer science; Enterprise data management; Data management; Workflow; Metadata; Data dictionary; Data element; Data virtualization; Information governance; Data science; Database; World Wide Web; Business; Information system; Engineering; Management information systems; Marketing","score_opus":0.6289315489095745,"score_gpt":0.5585743379486544,"score_spread":0.07035721096092007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890629418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6255275,0.0001420787,0.2684773,0.026619272,0.01195593,0.0027640038,0.06250773,0.00011636862,0.0018898302],"genre_scores_gemma":[0.92136294,0.0001720303,0.043995775,0.001636655,0.0012537014,0.0000040029,0.030601712,0.000024963738,0.00094825355],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9941772,0.00017233417,0.0009574836,0.0017132555,0.0026699866,0.00030974663],"domain_scores_gemma":[0.99165857,0.00048074374,0.0013139705,0.0052657686,0.0010829361,0.00019803956],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.018566955,0.00014594833,0.00018474771,0.0006010346,0.0005112174,0.0036981825,0.023369517,0.000037536574,0.0001685616],"category_scores_gemma":[0.04225088,0.00012879282,0.000007608485,0.0014004098,0.0002271643,0.036069535,0.015676292,0.00018058492,0.00006658001],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021666187,0.00051213545,0.28479153,0.000027735605,0.000105332765,0.00006103391,0.003127293,0.00043291075,0.00028211207,0.008885178,0.45681468,0.2447434],"study_design_scores_gemma":[0.0009094501,0.00016234469,0.13263927,0.00014903447,0.000032691503,0.00010622966,0.007944775,0.28939858,0.000011555231,0.0035781786,0.56464934,0.0004185213],"about_ca_topic_score_codex":0.0026783647,"about_ca_topic_score_gemma":0.0065397792,"teacher_disagreement_score":0.2958354,"about_ca_system_score_codex":0.00012703617,"about_ca_system_score_gemma":0.00077411224,"threshold_uncertainty_score":0.9973361},"labels":[],"label_agreement":null},{"id":"W2890636549","doi":"10.23889/ijpds.v3i4.736","title":"Lessons from the past: A window on the future","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Data sharing; Data governance; Data science; Corporate governance; Big data; Identification (biology); Computer science; Presentation (obstetrics); Knowledge management; Business","score_opus":0.600341306554498,"score_gpt":0.6396671413743392,"score_spread":0.0393258348198412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890636549","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32283452,0.0000521385,0.003915577,0.66453904,0.00655322,0.00037390005,0.000509892,0.000017561171,0.0012041518],"genre_scores_gemma":[0.9805374,0.000099937286,0.001941736,0.0072489413,0.00954644,0.00000505975,0.000126367,0.000007700197,0.00048642702],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99678904,0.00005495972,0.00030392702,0.0003115866,0.002350833,0.00018964571],"domain_scores_gemma":[0.9929476,0.004223612,0.00018902126,0.00087819237,0.0016370591,0.00012452615],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0062737362,0.00006905086,0.000077009034,0.00008100884,0.0008450488,0.00040179686,0.0031207076,0.000064357286,0.0002592356],"category_scores_gemma":[0.015895423,0.00003292621,0.00005350488,0.00025012015,0.00068978843,0.0004941486,0.0004810079,0.0008897896,0.00007057158],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011074923,0.000264556,0.16808623,0.000005885292,0.00019470087,0.000023266766,0.0006667101,0.0000305466,0.002770158,0.64375824,0.09925591,0.083836325],"study_design_scores_gemma":[0.00076598534,0.00024736443,0.72628844,0.00022905825,0.00002704398,0.000084529915,0.00038271316,0.0069096615,0.00023141084,0.13383605,0.13090488,0.00009284965],"about_ca_topic_score_codex":0.0001001835,"about_ca_topic_score_gemma":0.00039449832,"teacher_disagreement_score":0.65770286,"about_ca_system_score_codex":0.00011378129,"about_ca_system_score_gemma":0.00039725858,"threshold_uncertainty_score":0.9923941},"labels":[],"label_agreement":null},{"id":"W2890638138","doi":"10.23889/ijpds.v3i4.708","title":"Methods for identifying health state transitions from administrative data: the case of metastasis in prostate cancer","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University Health Network; University of Toronto","funders":"","keywords":"Medicine; False positive paradox; Bone metastasis; Malignancy; Population; Identification (biology); Prostate cancer; Cancer; Metastasis; Medical record; Medical prescription; Cancer registry; Data mining; Computer science; Internal medicine; Machine learning","score_opus":0.34104380065959883,"score_gpt":0.6057042374598454,"score_spread":0.26466043680024653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890638138","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28630987,0.0005982836,0.65232635,0.01909671,0.0075606336,0.0025974645,0.031327073,0.000031116953,0.00015249764],"genre_scores_gemma":[0.8943135,0.00030989273,0.10423565,0.00022542702,0.00034814308,0.000042316697,0.0004873799,0.00000743765,0.00003025165],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99769104,0.00033730705,0.0006442729,0.00042880294,0.00060458935,0.0002939713],"domain_scores_gemma":[0.9976279,0.00033314916,0.0006271097,0.0004875559,0.000830179,0.0000941172],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.010350758,0.000092249116,0.00016106809,0.00030291447,0.0013025552,0.0004437613,0.0023005488,0.000016552103,0.00003394976],"category_scores_gemma":[0.0008323874,0.000074646094,0.000051805542,0.0006279846,0.00072452374,0.0031226533,0.0002324741,0.00011220286,5.7262525e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040570062,0.00033225116,0.03007099,0.000045481494,0.00049345684,0.000042496205,0.042743027,0.0007992244,0.00035837176,0.06086224,0.0036369069,0.8602099],"study_design_scores_gemma":[0.0049695508,0.00053596386,0.29473472,0.0007676624,0.0004344338,0.00016275696,0.065634504,0.1711226,0.00088640815,0.24583043,0.21372002,0.0012009563],"about_ca_topic_score_codex":0.034729697,"about_ca_topic_score_gemma":0.14308459,"teacher_disagreement_score":0.8590089,"about_ca_system_score_codex":0.0002032892,"about_ca_system_score_gemma":0.00064625184,"threshold_uncertainty_score":0.9999976},"labels":[],"label_agreement":null},{"id":"W2890656543","doi":"10.23889/ijpds.v3i4.856","title":"Prenatal exposure to the 2009 pandemic H1N1 influenza vaccine on health outcomes in children","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa; Institute for Clinical Evaluative Sciences; Children's Hospital of Eastern Ontario; Ottawa Hospital","funders":"","keywords":"Medicine; Vaccination; Confidence interval; Confounding; Pandemic; Relative risk; Influenza vaccine; Pediatrics; Herd immunity; Cohort; Propensity score matching; Cohort study; H1n1 pandemic; Otitis; Demography; Environmental health; Immunology; Coronavirus disease 2019 (COVID-19); Internal medicine; Disease","score_opus":0.14845176744035615,"score_gpt":0.5006102293653378,"score_spread":0.3521584619249817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890656543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9812836,0.00012702392,0.00054273295,0.015687477,0.0009643416,0.0008144122,0.00049869117,0.000021591315,0.00006012905],"genre_scores_gemma":[0.9879433,0.000057917972,0.0013862519,0.009533454,0.00082913745,0.000016751164,0.000105020554,0.000009907516,0.00011824609],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99736226,0.000041786978,0.0005011178,0.0003517628,0.0013745803,0.000368502],"domain_scores_gemma":[0.9983774,0.00011142795,0.00019207255,0.0004996256,0.0006360295,0.00018346701],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002415564,0.00011841677,0.0001840451,0.00055546087,0.00046680667,0.00016742322,0.0014671036,0.00002665593,0.000037260703],"category_scores_gemma":[0.0035936937,0.00007258496,0.00003986762,0.0004204826,0.00010075053,0.0008497962,0.0004567511,0.00027407912,0.000050235612],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003608426,0.00006792484,0.9725486,0.0000030938688,0.00004724155,0.0000016168603,0.000202207,0.00024927026,0.00006276333,0.00029974864,0.005732292,0.020424422],"study_design_scores_gemma":[0.0014278049,0.00048153312,0.9881886,0.00013418571,0.000004993008,0.000095352596,0.00003808516,0.0009063909,0.000057056808,0.000191539,0.008400262,0.000074185395],"about_ca_topic_score_codex":0.0004938875,"about_ca_topic_score_gemma":0.0005562301,"teacher_disagreement_score":0.020350236,"about_ca_system_score_codex":0.00038725813,"about_ca_system_score_gemma":0.0003099333,"threshold_uncertainty_score":0.43022466},"labels":[],"label_agreement":null},{"id":"W2890667787","doi":"10.23889/ijpds.v3i4.1022","title":"Alberta's Data Mobilization Strategy: Leveraging Linked Data for Innovation","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health","funders":"","keywords":"Business; Data access; Data quality; Health data; Private sector; Stakeholder; Health care; Public relations; Marketing; Economics; Political science; Computer science; Database; Economic growth","score_opus":0.7841675662632437,"score_gpt":0.6647130923013346,"score_spread":0.11945447396190911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890667787","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13553387,0.00006929131,0.81614417,0.028743079,0.0097014755,0.0022828314,0.006113751,0.000087007196,0.001324523],"genre_scores_gemma":[0.91401047,0.00008780527,0.046454057,0.0009814103,0.0032370323,0.000009826042,0.03403316,0.000026188101,0.0011600341],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99556434,0.000035462384,0.00095416675,0.0010101923,0.0021084507,0.00032737822],"domain_scores_gemma":[0.9865858,0.0023539448,0.00058739044,0.0033687886,0.0069213416,0.0001827349],"candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.01308931,0.00012455496,0.00017285708,0.00055058865,0.0006145827,0.0006651749,0.0068383156,0.00013004804,0.00010326323],"category_scores_gemma":[0.07564697,0.000110604764,0.000024164754,0.00084315613,0.00043488963,0.0055239336,0.0024921065,0.00052258954,0.000016408145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003516123,0.0012672502,0.11896897,0.00036298335,0.000640062,0.00002108258,0.00052439293,0.0009706788,0.028211761,0.30986574,0.11359192,0.42205903],"study_design_scores_gemma":[0.0018552382,0.00029656026,0.026579142,0.00028772186,0.00005557416,0.000088264955,0.00011005907,0.86811656,0.00019862718,0.046036463,0.05618492,0.00019085898],"about_ca_topic_score_codex":0.00044447006,"about_ca_topic_score_gemma":0.0010208781,"teacher_disagreement_score":0.8671459,"about_ca_system_score_codex":0.00020441267,"about_ca_system_score_gemma":0.0014992446,"threshold_uncertainty_score":0.99853516},"labels":[],"label_agreement":null},{"id":"W2890678350","doi":"10.23889/ijpds.v3i4.1011","title":"Data linkage to build detailed return-to-work trajectories for work disability research","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Workers' compensation; Workforce; Work (physics); Context (archaeology); Population; Business; Compensation (psychology); Medicine; Actuarial science; Psychology; Environmental health; Economics; Engineering; Economic growth","score_opus":0.48215701861234206,"score_gpt":0.6399370753878652,"score_spread":0.1577800567755231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890678350","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79179114,0.00005678771,0.09479031,0.07078525,0.021341998,0.0077446583,0.0127286855,0.000100422636,0.0006607683],"genre_scores_gemma":[0.9435714,0.000013741937,0.044869535,0.0010123308,0.007072614,0.0002470506,0.0023893237,0.000027327193,0.00079671957],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99366224,0.0004198132,0.001082539,0.0010168552,0.0027084602,0.0011100987],"domain_scores_gemma":[0.98759145,0.0037905674,0.0002647128,0.0018258824,0.005641542,0.00088584836],"candidate_categories":["metaresearch","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.022572458,0.00015474675,0.00022977304,0.00052087667,0.004350053,0.0002971061,0.0067424723,0.00012619093,0.0002947228],"category_scores_gemma":[0.033427563,0.00013062847,0.000045842502,0.001977736,0.00047083426,0.0022146935,0.0025129619,0.00079027907,0.00021958629],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040716007,0.00014490382,0.85791814,0.00006845703,0.00002808483,0.0000014882942,0.0007647643,0.000050098042,0.00015112422,0.0045245015,0.091978535,0.04029831],"study_design_scores_gemma":[0.00066175696,0.0002727772,0.75078505,0.00029967478,0.000006280265,0.0000030302504,0.00025141187,0.0033539485,0.000017661192,0.0034605863,0.24072053,0.00016730897],"about_ca_topic_score_codex":0.00038640172,"about_ca_topic_score_gemma":0.0021621448,"teacher_disagreement_score":0.15178023,"about_ca_system_score_codex":0.0009306781,"about_ca_system_score_gemma":0.0016362298,"threshold_uncertainty_score":0.99863154},"labels":[],"label_agreement":null},{"id":"W2890681477","doi":"10.23889/ijpds.v3i4.741","title":"Extracting primary care records for prostate cancer patients in the CHHiP multicentre randomised control trial: A healthcare data linkage study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Cancer Research","funders":"","keywords":"Medicine; Prostate cancer; Comorbidity; Population; Medical prescription; Medical record; Diabetes mellitus; Randomized controlled trial; Clinical trial; Cancer; Health care; Radiation therapy; Family medicine; Physical therapy; Internal medicine","score_opus":0.11853279635179889,"score_gpt":0.3937526645700024,"score_spread":0.27521986821820354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890681477","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9720329,0.00052413385,0.0032395609,0.0022126401,0.007084801,0.0045654164,0.010139018,0.000012568427,0.00018897805],"genre_scores_gemma":[0.9956234,0.0001418343,0.0008528882,0.00076454825,0.001421849,0.00013036963,0.0010060745,0.000015838828,0.000043180244],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99779296,0.000037485035,0.0010475043,0.0005979761,0.00019185085,0.00033219485],"domain_scores_gemma":[0.9973725,0.00025683665,0.0011092449,0.0006072805,0.00057241437,0.00008171063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039499016,0.00013307472,0.00029331853,0.00026957248,0.00048630327,0.0005378051,0.0026924226,0.000046132976,0.000020286892],"category_scores_gemma":[0.0019349246,0.000115134186,0.000054329976,0.00018409059,0.000085879365,0.0031916604,0.00020903828,0.0001784334,0.0000058460064],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.025991036,0.0005256847,0.89233965,0.000040675004,0.000084119056,0.000002093128,0.005661607,0.000115497554,0.000004015364,0.0010408269,0.0014385005,0.072756305],"study_design_scores_gemma":[0.19710708,0.0008646852,0.7276768,0.00013251297,0.000034544537,0.0000039733036,0.0015726072,0.028544875,0.0000030645929,0.0023335118,0.041326974,0.0003993473],"about_ca_topic_score_codex":0.0023383058,"about_ca_topic_score_gemma":0.003691345,"teacher_disagreement_score":0.17111604,"about_ca_system_score_codex":0.0004903667,"about_ca_system_score_gemma":0.00025606554,"threshold_uncertainty_score":0.51860666},"labels":[],"label_agreement":null},{"id":"W2890714551","doi":"10.23889/ijpds.v3i4.931","title":"Cross-sector service use among youth and young adults involved in the Alberta provincial justice system","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Government of Alberta","funders":"","keywords":"Economic Justice; Criminal justice; Service (business); Mental health; Business; Psychology; Economic growth; Political science; Criminology; Psychiatry; Economics; Marketing","score_opus":0.5372409681858877,"score_gpt":0.614040085552202,"score_spread":0.07679911736631428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890714551","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9891935,0.000002263734,0.001481879,0.0022218174,0.005079865,0.0009598415,0.0008307209,0.000019923506,0.00021018914],"genre_scores_gemma":[0.9925725,0.000004243245,0.0011712891,0.004361091,0.0015694206,0.00004143748,0.00015501592,0.000010573645,0.00011446495],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9962455,0.00036631306,0.0010361127,0.00048143105,0.0013240934,0.0005465601],"domain_scores_gemma":[0.9954562,0.0012160207,0.0007604466,0.00048382263,0.0018703736,0.00021312125],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0072933985,0.00012663325,0.00013372528,0.00036631088,0.0022849808,0.0005937266,0.0023938417,0.00006955238,0.000045524757],"category_scores_gemma":[0.008175452,0.00009270359,0.000018075289,0.00074894243,0.0003223097,0.005623424,0.000508824,0.0003491955,0.00003159292],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013939128,0.00001408306,0.97047794,0.00008336409,0.00000431678,0.0000018320989,0.02571314,0.000010051275,0.000035791873,0.002541107,0.0005971406,0.0003818718],"study_design_scores_gemma":[0.0011293185,0.000045353223,0.9525776,0.00024878577,0.000015717178,0.000023090648,0.010909645,0.032374434,0.0000039567108,0.000067956535,0.0024893684,0.00011478062],"about_ca_topic_score_codex":0.04118582,"about_ca_topic_score_gemma":0.111464545,"teacher_disagreement_score":0.07027873,"about_ca_system_score_codex":0.0004689118,"about_ca_system_score_gemma":0.00080448174,"threshold_uncertainty_score":0.9990139},"labels":[],"label_agreement":null},{"id":"W2890715558","doi":"10.23889/ijpds.v3i4.820","title":"Spatial epidemiology of premature mortality in Ontario, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Cancer Care Ontario; University of Toronto","funders":"","keywords":"Demography; Population; Overweight; Medicine; Epidemiology; Population health; Geography; Environmental health; Obesity; Gerontology","score_opus":0.1547768920984266,"score_gpt":0.4714972169210843,"score_spread":0.3167203248226577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890715558","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98368716,0.000022896207,0.0015808515,0.0057843053,0.007496365,0.0001684939,0.0001674102,0.0000045830484,0.0010879559],"genre_scores_gemma":[0.99688214,0.00001076363,0.0014737899,0.0008882912,0.00051217974,0.0000015443355,0.00005828117,0.0000019353006,0.00017109788],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99832433,0.00008686881,0.00047721315,0.00018349256,0.0006553514,0.00027272615],"domain_scores_gemma":[0.9986338,0.0002625316,0.00030048407,0.00017971394,0.0004971032,0.00012633864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040799496,0.000047185607,0.00013075932,0.00010593284,0.00035098768,0.000031978234,0.0012867544,0.000039116105,0.00024758605],"category_scores_gemma":[0.004436193,0.000042411044,0.000020600077,0.00013780117,0.0003041235,0.00086367736,0.000119541364,0.00012673257,6.071153e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000149500165,0.000009509243,0.977393,0.0000024508206,0.000004210631,9.701109e-7,0.00036011662,0.000025857877,0.0000014350849,0.0196646,0.0013869004,0.001136024],"study_design_scores_gemma":[0.00012218462,0.000009982154,0.9655843,0.00003066683,0.0000021714566,0.0000025209308,0.00017307614,0.0010152466,0.0000041787994,0.0041381475,0.02887436,0.000043162894],"about_ca_topic_score_codex":0.9979399,"about_ca_topic_score_gemma":0.99984574,"teacher_disagreement_score":0.02748746,"about_ca_system_score_codex":0.0008133547,"about_ca_system_score_gemma":0.0040672794,"threshold_uncertainty_score":0.7215179},"labels":[],"label_agreement":null},{"id":"W2890723064","doi":"10.23889/ijpds.v3i4.814","title":"Ontario’s stroke report cards: Cross-continuum data linkage allows evaluation of system of care","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Rehabilitation Institute; Health Sciences Centre; Sunnybrook Health Science Centre; Royal Victoria Hospital; Kingston Health Sciences Centre","funders":"","keywords":"Report card; Knowledge translation; Stroke (engine); Best practice; Interdependence; Linkage (software); Balanced scorecard; Medicine; Medical emergency; Business; Psychology; Computer science; Process management; Knowledge management; Political science; Engineering","score_opus":0.10601405847907469,"score_gpt":0.447654574613484,"score_spread":0.3416405161344093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890723064","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9783839,0.000084707266,0.009080779,0.00014640485,0.0043860227,0.00064731046,0.0017672435,0.000015569729,0.005488094],"genre_scores_gemma":[0.9815266,0.0000034416314,0.012927677,0.000027085765,0.00075453776,0.00000532057,0.004159779,0.000009343656,0.00058617553],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9954481,0.00002698999,0.0009507246,0.000501092,0.0028967918,0.00017630616],"domain_scores_gemma":[0.99177444,0.000038929247,0.00106804,0.0014824957,0.0055438667,0.00009224846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004908815,0.00011017617,0.00024241467,0.00033784777,0.0001367832,0.00010605402,0.0021967888,0.00004878336,0.00007972966],"category_scores_gemma":[0.0017215986,0.0000975379,0.00006401206,0.00017462522,0.00026933232,0.0016255813,0.0009399755,0.00012732152,0.000003385254],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065797794,0.00015827215,0.9308221,0.00024194531,0.00061111734,0.00006182312,0.0012686676,0.00024270237,0.020743389,0.000497572,0.016209288,0.028485144],"study_design_scores_gemma":[0.0050490675,0.00045278727,0.8181661,0.001287118,0.0010259587,0.0014526551,0.0016703062,0.09480973,0.011166657,0.000063831925,0.06455218,0.00030364172],"about_ca_topic_score_codex":0.0029053062,"about_ca_topic_score_gemma":0.0033949015,"teacher_disagreement_score":0.11265604,"about_ca_system_score_codex":0.0008195281,"about_ca_system_score_gemma":0.00096048444,"threshold_uncertainty_score":0.43919733},"labels":[],"label_agreement":null},{"id":"W2890735078","doi":"10.23889/ijpds.v3i4.766","title":"Linking population-based survey and cancer registry data to examine the association between behaviours consistent with cancer prevention recommendations and cancer risk in Ontario","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Cancer Care Ontario","funders":"","keywords":"Cancer prevention; Medicine; Cancer registry; Cancer; Environmental health; Population; Gerontology; Cohort; Hazard ratio; Demography; Confidence interval; Internal medicine","score_opus":0.1732671198157453,"score_gpt":0.43029959898005976,"score_spread":0.2570324791643145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890735078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9837246,0.00019806947,0.00095993734,0.009671201,0.0007504998,0.00045120067,0.004227179,0.000007736922,0.000009571989],"genre_scores_gemma":[0.9914393,0.00046141914,0.0026797792,0.00033939414,0.00048465445,0.000042158685,0.004370963,0.000009377246,0.0001729757],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99824184,0.00006456708,0.00038786247,0.00042577158,0.000691689,0.00018827729],"domain_scores_gemma":[0.99797904,0.00027727403,0.00048,0.0003091929,0.0008442065,0.00011029435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020811118,0.00010940423,0.00016744624,0.00017688378,0.0006040874,0.00022982607,0.00046465782,0.000042035586,0.000051766216],"category_scores_gemma":[0.0006958906,0.000081381186,0.000015537235,0.0002721622,0.000094417584,0.00078143104,0.00025347085,0.00021545605,3.0823077e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014070424,0.000037163492,0.9855963,0.000004138856,0.00006434161,5.595943e-7,0.000053063744,0.00009626768,0.0000138901105,0.00002556514,0.001092236,0.012875786],"study_design_scores_gemma":[0.001068405,0.00009094881,0.9909545,0.00044110222,0.00012256221,0.000006805267,0.00003838941,0.0022756138,0.000006233962,0.00010772451,0.004786008,0.00010171497],"about_ca_topic_score_codex":0.28333881,"about_ca_topic_score_gemma":0.75124,"teacher_disagreement_score":0.4679012,"about_ca_system_score_codex":0.001003274,"about_ca_system_score_gemma":0.00048441367,"threshold_uncertainty_score":0.72143346},"labels":[],"label_agreement":null},{"id":"W2890743342","doi":"10.23889/ijpds.v3i4.1024","title":"A big data analytics platform to support simulation modeling for osteoarthritis care pathways","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Online analytical processing; Computer science; Data warehouse; Analytics; Data cube; Big data; Data analysis; Data science; Decision support system; Data management; Dice; Data mining; Database; Statistics","score_opus":0.692944808603131,"score_gpt":0.5791936113854909,"score_spread":0.11375119721764015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890743342","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17688026,0.000014824792,0.811358,0.0022563282,0.004759675,0.0009673537,0.0036605815,0.00003453481,0.000068445144],"genre_scores_gemma":[0.91535646,0.000010455425,0.068668075,0.0012513093,0.0037781256,0.000009843307,0.010876959,0.00002016206,0.00002861186],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966956,0.000013379035,0.0011487304,0.00062411407,0.0012219064,0.00029626297],"domain_scores_gemma":[0.99418384,0.00038888937,0.0004288266,0.0009479819,0.003784102,0.00026634336],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002763048,0.0001316782,0.00018538686,0.00044516235,0.0004804807,0.00038978484,0.0016108324,0.000054850992,0.000045929624],"category_scores_gemma":[0.014068925,0.00012547037,0.000058134545,0.00035200792,0.00007887179,0.0034946809,0.0006977659,0.00013755406,0.000019386238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014594708,0.00010651207,0.0085675055,0.000029339373,0.00007420554,0.000008616403,0.0005263368,0.036734853,0.0014853432,0.00065363455,0.0037560351,0.9465982],"study_design_scores_gemma":[0.0021434715,0.0008176021,0.0019810684,0.00008398175,0.00010618843,0.00009203524,0.00060355687,0.9611997,0.000080322214,0.00094575033,0.031792946,0.000153376],"about_ca_topic_score_codex":0.000115128016,"about_ca_topic_score_gemma":0.00059424597,"teacher_disagreement_score":0.94644475,"about_ca_system_score_codex":0.00030942485,"about_ca_system_score_gemma":0.00070159213,"threshold_uncertainty_score":0.994236},"labels":[],"label_agreement":null},{"id":"W2890782223","doi":"10.23889/ijpds.v3i4.976","title":"Prescription Opioid Use and Concurrent Psychotropic Drug Use During Pregnancy: A Population-Based Retrospective Cohort Study Utilizing Linked Administrative Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Prenatal Substance Exposure Effects","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Medicine; Medical prescription; Pregnancy; Opioid; Population; Pharmacoepidemiology; Retrospective cohort study; Cohort; Cohort study; Pediatrics; Obstetrics; Internal medicine; Environmental health; Pharmacology","score_opus":0.11729231849422841,"score_gpt":0.40860819518274716,"score_spread":0.29131587668851877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890782223","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9904086,0.00008534933,0.003642679,0.00018498082,0.0029391034,0.0017847134,0.0008898351,0.000056562276,0.000008167287],"genre_scores_gemma":[0.99283236,0.0000274506,0.0042476696,0.000051714134,0.0006009548,0.00003009966,0.0021236383,0.0000211932,0.00006494589],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9964768,0.00010340819,0.0006316152,0.0009893352,0.0014967028,0.00030213164],"domain_scores_gemma":[0.9967351,0.0001833534,0.000534494,0.0010594816,0.0012483546,0.00023924133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000979037,0.0002169628,0.00027911784,0.0003717729,0.00059215573,0.0008741802,0.0011915466,0.000051915507,0.000025215124],"category_scores_gemma":[0.003938161,0.00019467725,0.00003726692,0.0003558136,0.0002298215,0.0075366474,0.00043690196,0.0003038888,0.000002873081],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030215038,0.00021270945,0.9960374,0.00001642244,0.00009099929,0.00002225041,0.0002678355,0.000009759949,0.0015332237,0.00021634198,0.00014080745,0.0011500862],"study_design_scores_gemma":[0.002140197,0.000308455,0.96481127,0.0005987863,0.00009373483,0.000081841215,0.00007482547,0.031302724,0.0002126803,0.000109665096,0.000096241696,0.00016958833],"about_ca_topic_score_codex":0.0005895368,"about_ca_topic_score_gemma":0.0009442364,"teacher_disagreement_score":0.031292964,"about_ca_system_score_codex":0.00053646497,"about_ca_system_score_gemma":0.00023733382,"threshold_uncertainty_score":0.84297395},"labels":[],"label_agreement":null},{"id":"W2890787836","doi":"10.23889/ijpds.v3i3.443","title":"Multi-province epidemiological research using linked administrative data: a case study from Canada.","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institut universitaire en santé mentale de Montréal; Cégep Marie-Victorin; Centre for Addiction and Mental Health; Women's College Hospital; University of Toronto; Manitoba Health; South Health Campus; Simon Fraser University; University of Manitoba; Alberta Hospital Edmonton","funders":"","keywords":"Comparability; Context (archaeology); Scope (computer science); Government (linguistics); Business; Investment (military); Information system; Health care; Data collection; Minimum Data Set; Data science; Computer science; Political science; Geography; Medicine; Politics","score_opus":0.6286096928129259,"score_gpt":0.5941129252567702,"score_spread":0.034496767556155716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890787836","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97860146,0.00003986964,0.008356747,0.00084544776,0.0017940915,0.0007080091,0.009609832,0.00002256786,0.000021981245],"genre_scores_gemma":[0.95527875,0.000005492739,0.040320106,0.0002568855,0.0013979223,0.000005118544,0.002677404,0.0000110462115,0.000047261583],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99590987,0.00028463898,0.00068614405,0.0009369647,0.0017899763,0.00039242796],"domain_scores_gemma":[0.9948595,0.0006660337,0.00035229026,0.0014679712,0.002248083,0.00040611372],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0057716216,0.00014461439,0.00026452352,0.00024069767,0.0008279444,0.00028614872,0.0029008812,0.00004289058,0.000086448024],"category_scores_gemma":[0.014531241,0.00011534393,0.000026677655,0.00040622996,0.0005455995,0.001982545,0.0016270325,0.00038903326,0.000007691299],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001139145,0.0010814746,0.95870084,0.000010112983,0.00031464014,0.0089535285,0.00030101705,0.000112136695,0.0028713867,0.00013402964,0.013922963,0.012458743],"study_design_scores_gemma":[0.00198196,0.00035496175,0.61797786,0.00010241585,0.000059393045,0.003155086,0.0018804272,0.36847547,0.000034764682,0.00013848835,0.0056292876,0.00020990378],"about_ca_topic_score_codex":0.3733717,"about_ca_topic_score_gemma":0.54236513,"teacher_disagreement_score":0.36836332,"about_ca_system_score_codex":0.00070406933,"about_ca_system_score_gemma":0.0040589073,"threshold_uncertainty_score":0.99376976},"labels":[],"label_agreement":null},{"id":"W2890804179","doi":"10.23889/ijpds.v3i4.622","title":"Association rule mining to identify potential under-coding of conditions in the problem list in primary care electronic medical records","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Association rule learning; Coding (social sciences); Medicine; Medical record; Medical diagnosis; Confidence interval; Data mining; Family medicine; Medical emergency; Computer science; Statistics; Mathematics; Internal medicine","score_opus":0.033696190442696554,"score_gpt":0.3872326723535957,"score_spread":0.35353648191089915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890804179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5273218,0.00002567328,0.4614758,0.008737415,0.0013690097,0.00036794215,0.00031057152,0.000022043248,0.00036976908],"genre_scores_gemma":[0.9594051,0.000016331504,0.0394288,0.00040259882,0.00027511094,0.000020721516,0.00042053452,0.0000040177742,0.000026787146],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99755,0.00005670396,0.00049373053,0.00034020774,0.0012936245,0.00026572356],"domain_scores_gemma":[0.99860513,0.0001536677,0.00030729602,0.00035737557,0.00051096245,0.00006556487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031732023,0.0000714838,0.00009636704,0.00043699512,0.0002942264,0.00047959198,0.0034187275,0.00004159378,0.000014339515],"category_scores_gemma":[0.0004900594,0.00006194484,0.000027620099,0.0008812769,0.00006827954,0.0022140073,0.00048982527,0.00017809286,0.0000042798747],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011406956,0.0010381012,0.20062795,0.00007686047,0.00014538903,0.00004554494,0.013936602,0.0049353302,0.013419151,0.2746689,0.019746996,0.4712451],"study_design_scores_gemma":[0.0010465404,0.00016656613,0.74275523,0.0003896431,0.000014885531,0.00017209168,0.0009869108,0.23292097,0.00020982535,0.016385414,0.0046785497,0.00027338692],"about_ca_topic_score_codex":0.00034943482,"about_ca_topic_score_gemma":0.0011029433,"teacher_disagreement_score":0.54212725,"about_ca_system_score_codex":0.0005759058,"about_ca_system_score_gemma":0.000482676,"threshold_uncertainty_score":0.6352903},"labels":[],"label_agreement":null},{"id":"W2890808093","doi":"10.23889/ijpds.v3i4.846","title":"Differential spatial distribution of hepatitis B virus by ethnicity in British Columbia, Canada: Expanded role of a large administrative cohort","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Hepatitis B Virus Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"BC Centre for Disease Control; University of British Columbia","funders":"","keywords":"Ethnic group; Demography; Cohort; Medicine; Hepatitis B virus; Population; Distribution (mathematics); Geography; Hepatitis B; Public health; Environmental health; Virology; Virus; Internal medicine; Pathology","score_opus":0.03176054488843035,"score_gpt":0.3552512899936862,"score_spread":0.3234907451052559,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890808093","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9809401,0.00003159276,0.005919122,0.00010307811,0.00074230356,0.00028233562,0.011947001,0.000004628267,0.000029827843],"genre_scores_gemma":[0.99748844,0.000101722515,0.00024312812,0.000042231695,0.00018599608,0.000008403073,0.0018843822,0.0000058029404,0.000039896924],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99777186,0.000035918332,0.0006308302,0.00026747098,0.0010856752,0.00020823993],"domain_scores_gemma":[0.99803805,0.00005880926,0.00042212426,0.00019131789,0.0011923928,0.000097315875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005122188,0.00007090411,0.00024627658,0.00006483508,0.00017904818,0.000080319194,0.0004970742,0.000039939303,0.00016010969],"category_scores_gemma":[0.0014188902,0.000094394985,0.000036151687,0.00019806417,0.00028188835,0.00052040647,0.00019268124,0.000119611424,3.8487607e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000742556,0.00015447405,0.9885599,0.0000065193058,0.000043818174,0.0000063184334,0.000056786557,8.7425974e-7,0.0049130265,0.000044866898,0.0022571199,0.0038820272],"study_design_scores_gemma":[0.0008502654,0.00018107527,0.9891681,0.00013204872,0.000025037596,0.000046875175,0.000038993658,0.0052808453,0.0033587823,0.0001411435,0.0006982445,0.00007859576],"about_ca_topic_score_codex":0.97109544,"about_ca_topic_score_gemma":0.9967886,"teacher_disagreement_score":0.025693193,"about_ca_system_score_codex":0.00043631895,"about_ca_system_score_gemma":0.0008521279,"threshold_uncertainty_score":0.38493156},"labels":[],"label_agreement":null},{"id":"W2890821170","doi":"10.23889/ijpds.v3i4.843","title":"Patterns of pharmacotherapies used to treat alcohol use disorders: A population-based administrative data study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Substance Abuse Treatment and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Acamprosate; Medical prescription; Medicine; Alcohol use disorder; Psychiatry; Mental health; Population; Disulfiram; Anxiety; Comorbidity; Addiction; Alcohol dependence; Mood; Naltrexone; Environmental health; Alcohol; Pharmacology; Internal medicine","score_opus":0.2936558541243027,"score_gpt":0.5034173639892496,"score_spread":0.20976150986494696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890821170","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99227875,0.000013175334,0.0043846066,0.0009344253,0.0008598704,0.00075509236,0.0007407387,0.000023646595,0.000009670018],"genre_scores_gemma":[0.9931828,0.00001047012,0.0043706913,0.00024139608,0.0003484355,0.0000117925265,0.0016973444,0.000014979746,0.00012209304],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977639,0.000035511457,0.00048791492,0.0004766452,0.0010419392,0.00019410026],"domain_scores_gemma":[0.9979532,0.00020541134,0.00030107464,0.00082211266,0.00056957925,0.00014862635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006231875,0.00014993465,0.00021465683,0.00043983746,0.0002296582,0.0001973642,0.0013841611,0.000023243525,0.00015111211],"category_scores_gemma":[0.00064714643,0.00011672098,0.0000469127,0.00032654905,0.00006778667,0.0024980186,0.00017277649,0.00007109325,0.0000061179985],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059428834,0.00043465005,0.99196273,0.000003114414,0.00009984656,0.0000056966087,0.00074527925,0.0000332151,0.0006660127,0.00005753631,0.00027844027,0.0051191607],"study_design_scores_gemma":[0.0041325428,0.00057313667,0.9870597,0.000094418,0.00012354949,0.000014374938,0.00067508064,0.0058428906,0.00073807454,0.000056704142,0.00055662164,0.00013291625],"about_ca_topic_score_codex":0.000564165,"about_ca_topic_score_gemma":0.002672886,"teacher_disagreement_score":0.0058096754,"about_ca_system_score_codex":0.000143654,"about_ca_system_score_gemma":0.00019147618,"threshold_uncertainty_score":0.47597432},"labels":[],"label_agreement":null},{"id":"W2890826217","doi":"10.23889/ijpds.v3i4.1012","title":"Investigating disparities in cancer by linking the Canadian Cancer Registry to survey and administrative databases: a collaboration between the Canadian Partnership Against Cancer and Statistics Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Partnership Against Cancer; Statistics Canada","funders":"","keywords":"General partnership; Record linkage; Cancer registry; Database; Cancer; Medicine; Business; Computer science; Environmental health; Finance; Population","score_opus":0.30802080621703976,"score_gpt":0.5436690987365502,"score_spread":0.23564829251951047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890826217","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7098783,0.0006362738,0.00030992058,0.18626173,0.003819775,0.0013045111,0.09755073,0.000008765644,0.00023000008],"genre_scores_gemma":[0.9733843,0.00021353448,0.0005661435,0.022880115,0.0007030005,0.00010041733,0.0019740139,0.000010144209,0.00016831227],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99791706,0.0002168893,0.0004847895,0.00030310228,0.00059477764,0.00048338552],"domain_scores_gemma":[0.99697095,0.0007859466,0.00035413733,0.0002380615,0.00111815,0.00053275586],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0026883224,0.0001166556,0.00014217895,0.0001582937,0.0040260055,0.00034896118,0.00081866846,0.000050654566,0.000022125474],"category_scores_gemma":[0.0022863592,0.000083425264,0.000004723224,0.00043983624,0.000334474,0.00076760206,0.00016291288,0.00042591675,3.7272628e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.000008144527,9.472686e-7,0.9055654,0.000013063912,0.000011651937,0.0000010939013,0.00073585706,0.00002372407,0.0000032491603,0.0010657589,0.08937261,0.0031985396],"study_design_scores_gemma":[0.0001832176,0.000011433271,0.9117549,0.00017030888,0.00000923273,0.0000011747978,0.0006274394,0.0019840423,0.0000031147808,0.0002087464,0.08493533,0.00011103938],"about_ca_topic_score_codex":0.99959046,"about_ca_topic_score_gemma":0.9999982,"teacher_disagreement_score":0.26350603,"about_ca_system_score_codex":0.003957951,"about_ca_system_score_gemma":0.04665789,"threshold_uncertainty_score":0.99986565},"labels":[],"label_agreement":null},{"id":"W2890833661","doi":"10.23889/ijpds.v3i4.817","title":"Population-based analysis of the effect of a comprehensive, systematic change in an emergency medical service resource allocation plan on 24 hour mortality","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Provincial Health Services Authority","funders":"","keywords":"Logistic regression; Population; Medicine; Demography; Family medicine; Environmental health; Medical emergency","score_opus":0.11879480365100813,"score_gpt":0.4407464198153351,"score_spread":0.32195161616432694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890833661","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966759,0.000049128106,0.00036218442,0.0010348251,0.0011454993,0.000492834,0.00021299433,0.000006930199,0.000019711479],"genre_scores_gemma":[0.998726,0.000012999735,0.000116910254,0.00028825007,0.00021784323,0.000015839498,0.0006125095,0.0000056883264,0.000003936213],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970049,0.00016730893,0.00079040177,0.00026470027,0.0016430506,0.00012960758],"domain_scores_gemma":[0.9975971,0.00016619373,0.00061402464,0.00052533473,0.0010150219,0.000082299695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016950434,0.00010858511,0.0003644814,0.0005841803,0.00016021202,0.000015626223,0.000984523,0.00004740552,0.000060452276],"category_scores_gemma":[0.0014245507,0.00007005471,0.00010742713,0.0013825136,0.000095441894,0.0004491438,0.000120634824,0.000116073694,6.453636e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018687295,0.00007973467,0.9971307,0.00046274986,0.00024119791,0.0000011965965,0.00025972372,0.0006270304,0.0003523178,0.00024154878,0.000076333024,0.00034061188],"study_design_scores_gemma":[0.00043936222,0.00022170949,0.84468704,0.0010549956,0.00036964173,0.000004365837,0.00008085311,0.15283808,0.00020981583,0.000022384476,0.000016044278,0.000055713597],"about_ca_topic_score_codex":0.0012629664,"about_ca_topic_score_gemma":0.0033531373,"teacher_disagreement_score":0.15244365,"about_ca_system_score_codex":0.000094317154,"about_ca_system_score_gemma":0.00007117998,"threshold_uncertainty_score":0.2856748},"labels":[],"label_agreement":null},{"id":"W2890833721","doi":"10.23889/ijpds.v3i4.965","title":"Attending Nurse Practitioners in Long-Term Care Homes Evaluation","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Long-term care; Health care; Emergency department; Christian ministry; Hospital bed; Family medicine; Medical emergency; Nursing; Emergency medicine","score_opus":0.15273481656580906,"score_gpt":0.5851314133005386,"score_spread":0.4323965967347296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890833721","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.974486,0.00021325528,0.0031617638,0.002966563,0.01505604,0.0012533714,0.00024371603,0.000046531295,0.0025727637],"genre_scores_gemma":[0.9930405,0.000061353734,0.0029801773,0.0004573241,0.0017324892,0.000041509178,0.0014883761,0.000012941619,0.00018533629],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9965955,0.00020113491,0.00074318785,0.0004326938,0.0015480843,0.0004794239],"domain_scores_gemma":[0.9959105,0.00020436019,0.00063476694,0.0004072202,0.0026752818,0.00016783873],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0037870836,0.00011634525,0.00013690392,0.00058759016,0.0013983496,0.00013764942,0.001428557,0.00008267811,0.00061418914],"category_scores_gemma":[0.002087992,0.000108332715,0.00002943724,0.00051678566,0.00017703288,0.0037099235,0.00022495084,0.000326468,0.00010346515],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015149853,0.000040049516,0.9511869,0.000037301623,0.000011293858,0.00000515294,0.0024693736,0.00017078673,0.00014280649,0.0030938492,0.0039867517,0.03870426],"study_design_scores_gemma":[0.0014418846,0.00007819771,0.9691681,0.0010267037,0.000020333115,0.000032571217,0.0052561103,0.013441398,0.000022615863,0.0013115131,0.008027221,0.00017333981],"about_ca_topic_score_codex":0.00045050602,"about_ca_topic_score_gemma":0.002163463,"teacher_disagreement_score":0.038530923,"about_ca_system_score_codex":0.0018400605,"about_ca_system_score_gemma":0.0008308085,"threshold_uncertainty_score":0.9999017},"labels":[],"label_agreement":null},{"id":"W2890844825","doi":"10.23889/ijpds.v3i4.1026","title":"Linking Provincial and Prospective Cohort Study Data to Estimate the Incidence and Healthcare Burden of Viral Gastroenteritis","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Viral gastroenteritis research and epidemiology","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Norovirus; Astrovirus; Medicine; Sapovirus; Rotavirus; Incidence (geometry); Rotavirus vaccine; Emergency department; Pediatrics; Population; Vaccination; Environmental health; Diarrhea; Internal medicine; Immunology; Virology; Outbreak","score_opus":0.07803808270933812,"score_gpt":0.4728584190186351,"score_spread":0.394820336309297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890844825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9882471,0.000026671882,0.0047866222,0.0052802144,0.0003916995,0.00085672224,0.00039774398,0.0000063312355,0.0000069120424],"genre_scores_gemma":[0.99050903,0.000028200822,0.0084552085,0.00020725408,0.00061323546,0.000011708993,0.00015648964,0.000005311244,0.000013552895],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982408,0.00006320789,0.00037426763,0.0004157303,0.000672844,0.00023310786],"domain_scores_gemma":[0.99846685,0.000031562988,0.00017502443,0.00042253,0.00072860764,0.00017541008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026328564,0.00007526038,0.00017184131,0.00015658684,0.0003262287,0.00014744776,0.0010899632,0.000016121372,0.0000050789195],"category_scores_gemma":[0.002666516,0.00005344549,0.000011379872,0.00011308543,0.00041204217,0.0010362639,0.001458809,0.00014817432,7.5864676e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000401879,0.000029059414,0.9861339,0.00000866852,0.000024525281,0.000009128334,0.00019368996,0.000005240608,0.00080132944,0.00010704452,0.00016786689,0.01211772],"study_design_scores_gemma":[0.0005650178,0.0013363486,0.9785491,0.00014714598,0.000015842357,0.00056624913,0.00016395884,0.018126184,0.000014939459,0.00028351965,0.0001962498,0.0000353942],"about_ca_topic_score_codex":0.001356005,"about_ca_topic_score_gemma":0.0014084878,"teacher_disagreement_score":0.018120943,"about_ca_system_score_codex":0.000083437626,"about_ca_system_score_gemma":0.00013695951,"threshold_uncertainty_score":0.31922615},"labels":[],"label_agreement":null},{"id":"W2890876014","doi":"10.23889/ijpds.v3i4.619","title":"Varenicline is More Effective than Nicotine Replacement Therapy During Pregnancy: Findings from the Smoking MUMS (Maternal Use of Medications and Safety) Study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Smoking Behavior and Cessation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Varenicline; Nicotine replacement therapy; Medicine; Smoking cessation; Pregnancy; Population; Nicotine; Obstetrics; Internal medicine; Environmental health","score_opus":0.0785433513082347,"score_gpt":0.40645500292581505,"score_spread":0.32791165161758035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890876014","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99528533,0.000040708906,0.0015945905,0.0012504475,0.0008992044,0.00063788495,0.00027542267,0.00001290892,0.0000034754846],"genre_scores_gemma":[0.99864054,0.00008883625,0.0005523879,0.00011057669,0.0003308191,0.000016711074,0.00020515225,0.00000962981,0.000045337678],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99799836,0.00003753691,0.00044945473,0.0003337568,0.0010476054,0.00013330566],"domain_scores_gemma":[0.99831915,0.0001776876,0.0003509269,0.00042685226,0.00065367593,0.00007168807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076536613,0.00010163351,0.00013436268,0.00017887824,0.00046388208,0.000175395,0.0005914488,0.000031089774,0.00008176238],"category_scores_gemma":[0.0004953875,0.00006863702,0.000034873105,0.00022251396,0.00021819813,0.0010532382,0.00021026563,0.00014092185,3.568423e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004374292,0.000116912735,0.989961,0.0000024012986,0.00010562458,0.0000016315515,0.0015058119,0.0000050788476,0.0023748192,0.000042297073,0.0000617272,0.0053852387],"study_design_scores_gemma":[0.0022922193,0.00024605214,0.99104726,0.00033424454,0.00009128074,0.00006291279,0.00025719524,0.0015736363,0.0037842263,0.000088912166,0.00015660557,0.00006546946],"about_ca_topic_score_codex":0.000658592,"about_ca_topic_score_gemma":0.000048147893,"teacher_disagreement_score":0.0053197695,"about_ca_system_score_codex":0.00012417824,"about_ca_system_score_gemma":0.00007004708,"threshold_uncertainty_score":0.3567853},"labels":[],"label_agreement":null},{"id":"W2890885556","doi":"10.23889/ijpds.v3i4.923","title":"Comparing two asthma diagnoses using a prospective cohort of young children","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Asthma and respiratory diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"False positive paradox; Medicine; Asthma; Cohen's kappa; Kappa; Medical diagnosis; Pediatrics; False positives and false negatives; Cohort; Positive predicative value; Predictive value; Internal medicine; Statistics; Pathology","score_opus":0.05664827059341418,"score_gpt":0.40712992394901776,"score_spread":0.35048165335560355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890885556","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9911245,0.000044673965,0.007236036,0.000052864212,0.00097488106,0.00026647336,0.00011450483,0.000011889855,0.00017417905],"genre_scores_gemma":[0.9941926,0.0000058777723,0.004632212,0.000057656664,0.0009705948,0.0000023531124,0.00011223608,0.000007170712,0.000019327796],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99851316,0.0000132869345,0.00032050925,0.00024732525,0.000763548,0.00014215738],"domain_scores_gemma":[0.99836063,0.000025926869,0.00027692094,0.0002320358,0.000988441,0.00011602994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053269154,0.0000751088,0.00014056073,0.00024957862,0.0002697294,0.000098532924,0.00058724184,0.000016324508,0.000039778737],"category_scores_gemma":[0.0006407956,0.00006083244,0.00004662525,0.00020792466,0.00031893674,0.0011071647,0.00019512617,0.00007454787,0.0000031013099],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010333807,0.00006975977,0.99527377,0.0000023937102,0.00004130279,0.000003237291,0.00003710022,0.000106716296,0.0016618518,0.0004322493,0.000098058656,0.002170216],"study_design_scores_gemma":[0.0007618387,0.00009842035,0.97339016,0.00011343052,0.000034084966,0.00035265813,0.000030073508,0.02378799,0.0010027672,0.00018873703,0.0001752156,0.00006461152],"about_ca_topic_score_codex":0.00021848602,"about_ca_topic_score_gemma":0.000045479374,"teacher_disagreement_score":0.023681274,"about_ca_system_score_codex":0.00013414932,"about_ca_system_score_gemma":0.0002365468,"threshold_uncertainty_score":0.24806748},"labels":[],"label_agreement":null},{"id":"W2890886173","doi":"10.23889/ijpds.v3i4.758","title":"What makes great data documentation?","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Manitoba Health","funders":"","keywords":"Documentation; Session (web analytics); Data presentation; Presentation (obstetrics); Resource (disambiguation); Population; Computer science; Data science; Library science; World Wide Web; Medicine","score_opus":0.18018888186869186,"score_gpt":0.5291111611317418,"score_spread":0.34892227926305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890886173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40216038,0.0011753594,0.052888244,0.30136606,0.22218736,0.0023932897,0.0038927244,0.0003451278,0.013591453],"genre_scores_gemma":[0.9696734,0.0011276515,0.012239905,0.0053708116,0.007101171,0.0000064609335,0.0013258348,0.0000135017235,0.0031412952],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974878,0.000058067097,0.00036623236,0.0003821983,0.0013529845,0.00035270624],"domain_scores_gemma":[0.9979725,0.0001684861,0.00023302704,0.0005881014,0.00081722124,0.00022068956],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0036355827,0.0000737266,0.000086064945,0.00019565944,0.0018881472,0.0029123866,0.0045073926,0.000034888333,0.0006361409],"category_scores_gemma":[0.0020738416,0.00006661877,0.000022698696,0.0002813227,0.0005009121,0.019458607,0.0005716558,0.0000849246,0.00005051646],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015215711,0.000110632915,0.17569447,0.000020187663,0.00007918752,0.000016276137,0.006682945,0.00003441063,0.000036761743,0.30207974,0.14852084,0.3665724],"study_design_scores_gemma":[0.00043556976,0.000026901913,0.11569834,0.000101579884,0.000014554485,0.000030658375,0.0043163183,0.005335958,0.000014138933,0.01141077,0.8624392,0.0001760124],"about_ca_topic_score_codex":0.0034847462,"about_ca_topic_score_gemma":0.006173252,"teacher_disagreement_score":0.7139184,"about_ca_system_score_codex":0.000230751,"about_ca_system_score_gemma":0.00055751007,"threshold_uncertainty_score":0.9994113},"labels":[],"label_agreement":null},{"id":"W2890888398","doi":"10.23889/ijpds.v3i4.831","title":"Designing and Implementing a Privacy Preserving Record Linkage Protocol","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Ontario Brain Institute; Indoc Research","funders":"","keywords":"Identifier; Computer science; Encryption; Unique identifier; Computer security; Code (set theory); Source code; Internet privacy; Set (abstract data type); Computer network","score_opus":0.25003608954734097,"score_gpt":0.5893802261652321,"score_spread":0.33934413661789115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890888398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4825869,0.000042347754,0.3735433,0.008456577,0.01519015,0.114710405,0.00031151442,0.00028137738,0.0048774467],"genre_scores_gemma":[0.82054555,0.000017624601,0.15242596,0.0012912076,0.009550564,0.014462072,0.00015745735,0.00006007445,0.0014894622],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99691516,0.000218607,0.00097410486,0.0004369609,0.0007522272,0.00070291874],"domain_scores_gemma":[0.99689907,0.00040118772,0.0008746473,0.00042045256,0.0011969741,0.0002076574],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008692011,0.000109804,0.00014369917,0.000315517,0.0027194007,0.00022430744,0.0017380917,0.00006131462,0.00019522538],"category_scores_gemma":[0.0034182253,0.00009557752,0.000020945565,0.00026554737,0.000097350334,0.0026753303,0.0010941206,0.0004049595,0.000021153694],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026505505,0.000050500894,0.83626866,0.00027616252,0.000049484923,0.000004635401,0.0029199186,0.0000047391236,0.008968237,0.004550429,0.015802624,0.13083954],"study_design_scores_gemma":[0.0031462752,0.00042941372,0.10776046,0.0014953539,0.000017398914,0.00011018495,0.0010825115,0.086086884,0.00032232483,0.007125756,0.79203254,0.0003909165],"about_ca_topic_score_codex":0.0007256473,"about_ca_topic_score_gemma":0.0005712337,"teacher_disagreement_score":0.7762299,"about_ca_system_score_codex":0.00043943274,"about_ca_system_score_gemma":0.0009407602,"threshold_uncertainty_score":0.9985789},"labels":[],"label_agreement":null},{"id":"W2890889223","doi":"10.23889/ijpds.v3i4.693","title":"A framework to facilitate interprovincial sharing of secondary health data in Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Health PEI; University of New Brunswick; Izaak Walton Killam Health Centre; Dalhousie University","funders":"","keywords":"Data sharing; Corporate governance; Unit (ring theory); Data governance; Health care; Public relations; Business; Information governance; Knowledge management; Political science; Information system; Medicine; Psychology; Data quality; Computer science; Marketing; Management information systems; Law; Alternative medicine","score_opus":0.6633079136260492,"score_gpt":0.6283620408085852,"score_spread":0.034945872817464085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890889223","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89378166,0.000058105237,0.06277688,0.033198267,0.0053736875,0.0006456395,0.0037145605,0.000010552164,0.00044063275],"genre_scores_gemma":[0.9644832,0.000024770645,0.032858726,0.0017846571,0.000452723,0.0000018796293,0.0002894547,0.0000063396046,0.00009825854],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9964829,0.000025899157,0.00078955275,0.00050071726,0.00193053,0.00027041588],"domain_scores_gemma":[0.9960091,0.0010418452,0.00026618023,0.0011272443,0.0012421872,0.00031342806],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008342124,0.00006686939,0.00017804957,0.00033738255,0.00013576107,0.000088576526,0.0038854133,0.000041236894,0.00011621019],"category_scores_gemma":[0.036328334,0.000060220114,0.000017707429,0.00038620617,0.00019324932,0.00094512803,0.0021917154,0.0007317189,0.000004815529],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015974711,0.00019778305,0.7425517,0.00018187142,0.00008114789,0.00004518042,0.0013811955,0.00016424332,0.0007397525,0.024876751,0.0077879312,0.22039498],"study_design_scores_gemma":[0.0014152878,0.0007209641,0.8316013,0.0023401142,0.000009705818,0.00013297467,0.00065948727,0.09378132,0.00017254746,0.05450084,0.014434104,0.00023131771],"about_ca_topic_score_codex":0.5633409,"about_ca_topic_score_gemma":0.89230716,"teacher_disagreement_score":0.32896623,"about_ca_system_score_codex":0.0010423783,"about_ca_system_score_gemma":0.010288728,"threshold_uncertainty_score":0.995322},"labels":[],"label_agreement":null},{"id":"W2890895329","doi":"10.23889/ijpds.v3i4.798","title":"International Comparison in Opiate Prescribing for New Users in Primary Care using Electronic Medical Record Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"","keywords":"Medical prescription; Medicine; Opiate; Family medicine; Primary care; Jurisdiction; Codeine; Psychiatry; Morphine; Nursing; Pharmacology; Law; Political science; Internal medicine","score_opus":0.1347870543941927,"score_gpt":0.451195855029873,"score_spread":0.31640880063568033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890895329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95866215,0.00024987018,0.031753022,0.0030417321,0.00465097,0.00091192464,0.0004947731,0.00002470271,0.00021085187],"genre_scores_gemma":[0.95546913,0.00012494031,0.03761259,0.00031606812,0.0010983471,0.000009034965,0.005299262,0.000019946561,0.000050703715],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99701035,0.000025198548,0.00070867036,0.0005994121,0.0012752686,0.00038110124],"domain_scores_gemma":[0.99841964,0.0000915286,0.0002806578,0.0005597554,0.0004748247,0.00017359678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012340449,0.0001372387,0.00022075333,0.0006361892,0.00014004008,0.00019667995,0.0024309081,0.000066049455,0.00006860231],"category_scores_gemma":[0.0013181544,0.00012966055,0.000039239054,0.00030845817,0.00010264541,0.0022067646,0.0006695579,0.00024604402,0.0000032469454],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010843967,0.00032384414,0.86880064,0.000036399637,0.00009347058,0.000016648319,0.0008333523,0.00047543156,0.0006889211,0.00066019484,0.0015865556,0.12540014],"study_design_scores_gemma":[0.0068136733,0.00030602812,0.31155154,0.0008588284,0.00005614303,0.00015668839,0.00052878866,0.64520425,0.0001288174,0.00072399696,0.033422124,0.00024915222],"about_ca_topic_score_codex":0.0013996023,"about_ca_topic_score_gemma":0.0022937325,"teacher_disagreement_score":0.6447288,"about_ca_system_score_codex":0.0016161537,"about_ca_system_score_gemma":0.0019130794,"threshold_uncertainty_score":0.5287404},"labels":[],"label_agreement":null},{"id":"W2890912884","doi":"10.23889/ijpds.v3i4.918","title":"Population Data Science: The science of data about people","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Economic and Social Research Council; Medical Research Council","keywords":"Population; Data science; Computer science; Informatics; Field (mathematics); Knowledge management; Political science; Sociology","score_opus":0.455399970034002,"score_gpt":0.5671411276653473,"score_spread":0.11174115763134529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890912884","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6802779,0.00017332142,0.23936515,0.020759583,0.03466048,0.0018161725,0.01900093,0.000107456035,0.003839048],"genre_scores_gemma":[0.9796689,0.00004121655,0.017247017,0.0003497965,0.00091324956,0.0000026400787,0.0015886262,0.000008610822,0.00017994209],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98524475,0.00012372588,0.001531387,0.0019014389,0.010614837,0.0005838763],"domain_scores_gemma":[0.9838299,0.0007521082,0.0016339084,0.008837012,0.004662163,0.00028486512],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["metaresearch","sts","scholarly_communication","open_science"],"category_scores_codex":[0.0662136,0.00017906488,0.000259587,0.0015180921,0.0031661368,0.0047003576,0.0679948,0.000036411187,0.00021545339],"category_scores_gemma":[0.035693772,0.00011793438,0.00004102695,0.005103541,0.004420639,0.044927873,0.020411199,0.00020691346,0.00007745716],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003061172,0.00045360686,0.066424474,0.00001751153,0.0000782916,0.000005041649,0.0015042115,0.0009628322,0.007895897,0.33701327,0.08182114,0.5035176],"study_design_scores_gemma":[0.0005081555,0.000086084365,0.5213321,0.00006551794,0.000036724865,0.00006572954,0.00093797996,0.3769083,0.00027517384,0.030144688,0.06936083,0.00027874712],"about_ca_topic_score_codex":0.0016693666,"about_ca_topic_score_gemma":0.0016888636,"teacher_disagreement_score":0.50323886,"about_ca_system_score_codex":0.00022619346,"about_ca_system_score_gemma":0.0012992116,"threshold_uncertainty_score":0.99828875},"labels":[],"label_agreement":null},{"id":"W2890967794","doi":"10.23889/ijpds.v3i4.830","title":"Patterns of opioid utilization in the 90-days post hospital discharge and risk of re-admissions and emergency department visits","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University Health Centre; McGill University","funders":"","keywords":"Medicine; Medical prescription; Opioid; Emergency medicine; Emergency department; Hospital discharge; Opioid overdose; Anesthesia; Internal medicine; (+)-Naloxone; Psychiatry","score_opus":0.043719455190228386,"score_gpt":0.383455523905271,"score_spread":0.3397360687150426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890967794","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99564385,0.00014687274,0.001581289,0.0010346106,0.00047255622,0.00032041743,0.0007804601,0.0000026984212,0.000017244001],"genre_scores_gemma":[0.99742347,0.0010138535,0.0010441925,0.00002854111,0.00008250934,0.0000048328566,0.00038600195,0.0000043757996,0.000012218608],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988015,0.000027565438,0.00036096203,0.00019459041,0.00051654596,0.00009881364],"domain_scores_gemma":[0.9989648,0.000040231855,0.00028709156,0.00021802919,0.00041374986,0.0000761207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059134304,0.00006963224,0.000098949466,0.00018785078,0.00013591938,0.0000312185,0.00033033532,0.000019356674,0.000051558873],"category_scores_gemma":[0.0007488995,0.000045814955,0.000022235905,0.00014489249,0.00004879262,0.00057639513,0.00013464004,0.000057950536,4.236497e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058253067,0.00020159507,0.99199444,0.000013873213,0.000027150927,0.0000010584835,0.0011407346,0.000002925975,0.0005031565,0.0007813489,0.00009517355,0.0051803105],"study_design_scores_gemma":[0.00062638003,0.00035405217,0.99350196,0.000099558616,0.000046474146,0.00002098649,0.0005476497,0.0035931028,0.0003457068,0.0005290606,0.0002909682,0.00004411979],"about_ca_topic_score_codex":0.00023537343,"about_ca_topic_score_gemma":0.00017403558,"teacher_disagreement_score":0.005136191,"about_ca_system_score_codex":0.00003408517,"about_ca_system_score_gemma":0.00008411157,"threshold_uncertainty_score":0.18682797},"labels":[],"label_agreement":null},{"id":"W2890980907","doi":"10.23889/ijpds.v3i4.663","title":"Cross-validation of Drug Use Records in Two Pharmaceutical Databases: A Population-based Study of Alberta’s Tomorrow Project Cohort","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; Alberta Health; University of Alberta","funders":"","keywords":"Medicine; Medical record; Database; Record linkage; Concordance; Cohort; Pharmaceutical Benefits Scheme; Family medicine; Population; Medical emergency; Environmental health; Internal medicine; Pharmacology; Medical prescription","score_opus":0.29642357256712293,"score_gpt":0.5646375358116785,"score_spread":0.2682139632445556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890980907","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99588877,0.000005712914,0.00096543087,0.00034245817,0.0014560994,0.0010167186,0.0002507156,0.000008463378,0.0000656183],"genre_scores_gemma":[0.99453485,0.0000060704333,0.003946291,0.00022591966,0.00022303045,0.000011777063,0.00094776554,0.000011378279,0.00009290976],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99691826,0.0001147982,0.0009906846,0.00040616284,0.0013596514,0.00021047001],"domain_scores_gemma":[0.9969812,0.0006426402,0.00067623943,0.00045246052,0.0011219212,0.00012553984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024012474,0.00012779397,0.00025714398,0.000639426,0.00013939802,0.00012955078,0.0007150682,0.000020861997,0.00015306268],"category_scores_gemma":[0.0045705847,0.000108393026,0.000054186316,0.0005782113,0.00015082576,0.0034778784,0.00019388516,0.00020721693,0.0000024087394],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012925715,0.0007968786,0.99541825,0.00002044912,0.00005133441,0.000004262102,0.00021650935,0.00044384855,0.00048140893,0.00014901522,0.000094525065,0.0010309354],"study_design_scores_gemma":[0.0042168275,0.0002556754,0.8452201,0.00013710673,0.00012591023,0.000030953568,0.00014621747,0.14680058,0.0018188829,0.00003651213,0.001093033,0.00011820721],"about_ca_topic_score_codex":0.023079723,"about_ca_topic_score_gemma":0.003141391,"teacher_disagreement_score":0.15019816,"about_ca_system_score_codex":0.00018408905,"about_ca_system_score_gemma":0.00031824518,"threshold_uncertainty_score":0.9834257},"labels":[],"label_agreement":null},{"id":"W2890982796","doi":"10.23889/ijpds.v3i4.916","title":"Mortality of mothers with opioid-use during pregnancy: an international comparison using linked mother-baby records for England and Ontario","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Prenatal Substance Exposure Effects","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Pregnancy; Incidence (geometry); Cumulative incidence; Population; Hazard ratio; Demography; Comorbidity; Proportional hazards model; Pediatrics; Obstetrics; Environmental health; Cohort; Confidence interval; Psychiatry","score_opus":0.10844790667144759,"score_gpt":0.3995123223301773,"score_spread":0.2910644156587297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890982796","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97594005,0.000022460663,0.021893123,0.000067515524,0.0013192355,0.00047613398,0.0002461251,0.000015358864,0.000020028428],"genre_scores_gemma":[0.9592051,0.0000065073627,0.039990228,0.000023493014,0.0004493184,0.0000065831837,0.00023453841,0.000015374431,0.000068892834],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982664,0.000021165726,0.00041848977,0.00037887995,0.0007284513,0.00018660571],"domain_scores_gemma":[0.99810475,0.00007827589,0.00043854484,0.0003462268,0.00089296006,0.00013925332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059699453,0.0001226724,0.00019611923,0.0002383255,0.00020558067,0.00019488427,0.00066137116,0.00004504466,0.000024927547],"category_scores_gemma":[0.00049548416,0.000101209895,0.00003246801,0.00012250064,0.00024945513,0.0030188404,0.00011406918,0.00012367363,2.2934196e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010983449,0.000107721055,0.9778307,0.00002463135,0.00011930554,0.0000060511,0.0010601897,0.00017978002,0.01539124,0.00018712816,0.000009541157,0.0039853426],"study_design_scores_gemma":[0.0027642369,0.0004765498,0.9193526,0.0005421293,0.000056855675,0.00023685583,0.000046661833,0.07251684,0.003054304,0.00023969672,0.00058192003,0.00013133037],"about_ca_topic_score_codex":0.0025893995,"about_ca_topic_score_gemma":0.009476475,"teacher_disagreement_score":0.07233707,"about_ca_system_score_codex":0.00033566423,"about_ca_system_score_gemma":0.00024684164,"threshold_uncertainty_score":0.52880955},"labels":[],"label_agreement":null},{"id":"W2890986727","doi":"10.23889/ijpds.v3i4.963","title":"Using Artificial Intelligence Technology for Social Determinants and Risk Factors Surveillance","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Social determinants of health; Population; Health equity; Population health; Disease; Risk factor; Disease surveillance; Environmental health; Business; Psychology; Medicine; Public health; Pathology","score_opus":0.32331855480005395,"score_gpt":0.531245212581993,"score_spread":0.20792665778193903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890986727","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8695322,0.000018694214,0.12557796,0.0018114145,0.002242142,0.00032654701,0.000463634,0.000017412613,0.000009992586],"genre_scores_gemma":[0.9852096,0.000025445144,0.013124212,0.000072876064,0.0014842004,0.000003444272,0.0000620037,0.000008483027,0.000009739824],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984368,0.000029487552,0.0004975222,0.00031880135,0.00043838425,0.00027902448],"domain_scores_gemma":[0.9980073,0.0000952352,0.00036557883,0.00018330137,0.00119587,0.00015274338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002341969,0.00008448368,0.00016880642,0.00040519022,0.000872925,0.00015496722,0.00048189252,0.00007768495,0.000009563336],"category_scores_gemma":[0.0025486506,0.00006966165,0.000028500031,0.00029810908,0.0002853553,0.00067577773,0.00011909376,0.00013332325,0.000001141841],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015982825,0.00004275197,0.68002087,0.00003206764,0.000027303722,0.0000024027302,0.00027915952,0.000004932744,0.00054396794,0.013870629,0.0001278425,0.30488825],"study_design_scores_gemma":[0.00067385193,0.0007867051,0.61101633,0.00018830196,0.00003742087,0.0008324583,0.0010555283,0.33678332,0.00091569696,0.029100958,0.018259734,0.00034970176],"about_ca_topic_score_codex":0.00085548655,"about_ca_topic_score_gemma":0.0004959457,"teacher_disagreement_score":0.3367784,"about_ca_system_score_codex":0.0001713522,"about_ca_system_score_gemma":0.0005997706,"threshold_uncertainty_score":0.67139214},"labels":[],"label_agreement":null},{"id":"W2890992935","doi":"10.23889/ijpds.v3i4.739","title":"Linkage of whole genome sequencing with administrative health, and electronic medical record data for the study of autism spectrum disorder: Feasibility, Opportunities and Challenges","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ontario Brain Institute; Institute for Clinical Evaluative Sciences; Holland Bloorview Kids Rehabilitation Hospital; Public Health Ontario; University of Toronto","funders":"","keywords":"Data science; Scope (computer science); Linkage (software); Human genetics; Identification (biology); Genetic data; Autism spectrum disorder; Medical genetics; Whole genome sequencing; Computer science; Autism; Psychology; Medicine; Genome; Psychiatry; Biology; Genetics; Population","score_opus":0.38593261035309384,"score_gpt":0.4605665107488772,"score_spread":0.07463390039578338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890992935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9163066,0.0010272092,0.009858922,0.06987153,0.0003057081,0.0014041646,0.0011786405,0.000013182349,0.000034053755],"genre_scores_gemma":[0.99613386,0.0031347943,0.00046494213,0.00007978641,0.00008118493,0.000010540576,0.00006391356,0.00000947994,0.00002150868],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9972796,0.00011841414,0.00047017797,0.00056983414,0.0012568532,0.00030515422],"domain_scores_gemma":[0.9980575,0.00055967993,0.00046648525,0.00066733296,0.00009606321,0.00015292886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031459748,0.000106639374,0.00018133098,0.00020413322,0.00058366073,0.00015039036,0.0025590444,0.000025574895,0.000014984548],"category_scores_gemma":[0.0015741123,0.00007341933,0.000012901546,0.00018888862,0.0009999459,0.0014345649,0.00095502107,0.00018484,1.7208602e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003102585,0.0021730685,0.0689384,0.00044860697,0.00035568775,0.000037077527,0.020715436,0.00007365568,0.004505375,0.6490499,0.00014653416,0.2504537],"study_design_scores_gemma":[0.013015252,0.035412215,0.35765794,0.0007936186,0.00015504332,0.0020925738,0.04702939,0.3472344,0.0008919192,0.1673298,0.027188208,0.0011996083],"about_ca_topic_score_codex":0.0003527998,"about_ca_topic_score_gemma":0.0051185307,"teacher_disagreement_score":0.48172006,"about_ca_system_score_codex":0.00010120628,"about_ca_system_score_gemma":0.0013389975,"threshold_uncertainty_score":0.47553837},"labels":[],"label_agreement":null},{"id":"W2890999860","doi":"10.23889/ijpds.v3i4.680","title":"Development of a Concept Dictionary to Standardize Definitions and Classifications While Working With a Common Repository of Linked Administrative Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Computer science; Consistency (knowledge bases); Variety (cybernetics); Quality (philosophy); Data science; Key (lock); Information retrieval; World Wide Web; Artificial intelligence","score_opus":0.27149780613449326,"score_gpt":0.4150943451276689,"score_spread":0.14359653899317565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890999860","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84059185,0.00010181038,0.15637921,0.00068806467,0.00054070243,0.00017899675,0.0012120886,0.000007696283,0.00029955365],"genre_scores_gemma":[0.8627594,0.0000089592795,0.13631076,0.00003129788,0.00012132076,0.0000038850276,0.00074554107,0.0000027805174,0.00001604419],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990536,0.000016594126,0.00029582734,0.00024033184,0.0003154336,0.00007823687],"domain_scores_gemma":[0.9989004,0.000037859998,0.00023116286,0.00032270138,0.00044357192,0.00006429052],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043571906,0.000052155392,0.00007701332,0.00008151308,0.00026793033,0.000042776996,0.00077789795,0.00003168103,0.0000025738848],"category_scores_gemma":[0.00032791766,0.0000424745,0.000009246309,0.00011767299,0.00049802306,0.00003867254,0.00034326638,0.000043634875,1.3082183e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024010781,0.0007338141,0.12880163,0.000039187264,0.0007581203,0.00000728147,0.005284531,0.00016549884,0.4946229,0.008959952,0.008792742,0.34943327],"study_design_scores_gemma":[0.002630767,0.0023756886,0.5756494,0.0008522004,0.00011826009,0.0005080592,0.0041212374,0.008152263,0.09892697,0.00088004884,0.30515563,0.0006294722],"about_ca_topic_score_codex":0.000009981641,"about_ca_topic_score_gemma":0.000099316705,"teacher_disagreement_score":0.44684777,"about_ca_system_score_codex":0.000021049722,"about_ca_system_score_gemma":0.00035203013,"threshold_uncertainty_score":0.20607305},"labels":[],"label_agreement":null},{"id":"W2891009223","doi":"10.23889/ijpds.v5i1.1343","title":"Can Linked Electronic Medical Record and Administrative Data Help Us Identify Those Living with Frailty?","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Frailty in Older Adults","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; University of Manitoba; University of British Columbia","funders":"","keywords":"Demographics; Medicine; Medical record; Population; Electronic medical record; Health care; Health data; Gerontology; Demography; Medical emergency; Environmental health; Internal medicine","score_opus":0.16025938690696495,"score_gpt":0.4435024283304713,"score_spread":0.28324304142350637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891009223","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8947057,0.0001584205,0.025472378,0.076392815,0.0013830939,0.0005983088,0.0010490314,0.00006939722,0.0001708445],"genre_scores_gemma":[0.9884551,0.00017307683,0.0074352454,0.0018199201,0.00093407964,0.0000043909386,0.0010507869,0.000015298732,0.00011206528],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99685633,0.000037221773,0.00043606944,0.0006300691,0.0017352292,0.00030505267],"domain_scores_gemma":[0.99793476,0.00024239467,0.0002814112,0.00054388464,0.0004982369,0.0004993016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012174429,0.0001378397,0.00018485126,0.00014810651,0.0002506376,0.0003624201,0.0021294921,0.00005756871,0.0001641715],"category_scores_gemma":[0.0072450303,0.000110132474,0.000021680242,0.0002902621,0.00024879805,0.0021231037,0.00078920636,0.0004557621,0.0000052669934],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000971581,0.00033498133,0.7929959,0.00009885639,0.00053666154,0.0003056692,0.0017368305,0.00005224582,0.0028809165,0.0035488938,0.016780486,0.17975694],"study_design_scores_gemma":[0.003089206,0.0013011857,0.7480406,0.0012356093,0.00015841004,0.003288586,0.000587718,0.21068037,0.00012558755,0.00084426417,0.03021595,0.00043249683],"about_ca_topic_score_codex":0.00023629102,"about_ca_topic_score_gemma":0.0012423693,"teacher_disagreement_score":0.21062812,"about_ca_system_score_codex":0.00016239,"about_ca_system_score_gemma":0.001303006,"threshold_uncertainty_score":0.8673501},"labels":[],"label_agreement":null},{"id":"W2891010287","doi":"10.23889/ijpds.v3i4.946","title":"Improving the Coding Completeness of Hypertension in Inpatient Administrative Health Data Using Machine Learning Methods","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Diagnosis code; Coding (social sciences); Logistic regression; Missing data; Computer science; Chart; Medicine; Random forest; Statistics; Machine learning; Data mining; Artificial intelligence; Population; Mathematics; Environmental health","score_opus":0.7960701398576574,"score_gpt":0.6418011185677549,"score_spread":0.1542690212899025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891010287","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2893102,0.00009953958,0.69698983,0.005521304,0.0065558758,0.00088627916,0.0005171261,0.000025480438,0.00009439647],"genre_scores_gemma":[0.92206657,0.00004597924,0.07578558,0.0009796518,0.00047237735,0.00000400224,0.0006270153,0.000006942591,0.00001186872],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99681425,0.0005305169,0.0012501068,0.00027464746,0.00080294616,0.00032752886],"domain_scores_gemma":[0.99608946,0.00084549916,0.0015079397,0.000475563,0.0009512117,0.00013030502],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.016349394,0.00008602744,0.00020058092,0.00030676296,0.0019608757,0.000056227065,0.0018168158,0.000045882323,0.00003810816],"category_scores_gemma":[0.0075700753,0.000059257294,0.000016649043,0.00037384796,0.0002080278,0.0016721612,0.0009042946,0.000538619,0.0000023563862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001116484,0.0002613643,0.39097154,0.0006635262,0.000070884504,0.000005029543,0.016693324,0.0022108639,0.010514616,0.01997153,0.0020572562,0.5554636],"study_design_scores_gemma":[0.0005393275,0.00011317573,0.028933434,0.00041278338,0.0000054002094,0.000020008552,0.0011769407,0.96414274,0.000040831343,0.00026137196,0.004290948,0.000063023224],"about_ca_topic_score_codex":0.0035118696,"about_ca_topic_score_gemma":0.0007300028,"teacher_disagreement_score":0.9619319,"about_ca_system_score_codex":0.0003394641,"about_ca_system_score_gemma":0.0011864074,"threshold_uncertainty_score":0.99933845},"labels":[],"label_agreement":null},{"id":"W2891023838","doi":"10.23889/ijpds.v3i4.654","title":"Determining Potentially Avoidable Emergency Medical Services (EMS) Transports: A Population Level Study Using Linked Administrative Data in Alberta Health Services (AHS)","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Triage; Emergency medical services; Medicine; Medical emergency; Population; Emergency medicine; Environmental health","score_opus":0.17081108406666962,"score_gpt":0.4788885398515234,"score_spread":0.3080774557848538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891023838","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.988258,0.00011992765,0.0039907238,0.0022524288,0.0038721317,0.00074373017,0.00068411,0.000022413484,0.000056546567],"genre_scores_gemma":[0.9890143,0.00013953567,0.0064864103,0.00037347784,0.0013098173,0.0000074221825,0.0025853117,0.000018094348,0.000065593376],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9955957,0.00007518358,0.0012572212,0.00078266737,0.001893269,0.0003959794],"domain_scores_gemma":[0.9974431,0.00005924149,0.00065992627,0.00070762576,0.0008667263,0.00026340949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026283849,0.00021227302,0.00034282196,0.00045126458,0.00075245096,0.0001409799,0.0022676573,0.000071098664,0.00018890585],"category_scores_gemma":[0.0004239363,0.00018607425,0.0000512121,0.00057513575,0.00010928234,0.0036073222,0.00055839453,0.0002554489,0.0000035426908],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002870696,0.0004937515,0.9842289,0.00011371112,0.00016734024,0.000052229156,0.0044768313,0.000075695,0.00024542317,0.00012854382,0.00020575819,0.009524729],"study_design_scores_gemma":[0.0016631674,0.00047884573,0.86711854,0.00089279126,0.00009375019,0.00022913422,0.004134399,0.12356618,0.0000117798445,0.00034675296,0.0012109935,0.0002536789],"about_ca_topic_score_codex":0.019989977,"about_ca_topic_score_gemma":0.08135215,"teacher_disagreement_score":0.12349048,"about_ca_system_score_codex":0.00020032955,"about_ca_system_score_gemma":0.0005987677,"threshold_uncertainty_score":0.98653597},"labels":[],"label_agreement":null},{"id":"W2891039173","doi":"10.23889/ijpds.v3i4.668","title":"Data Byte: An Insight on Fetal Alcohol Spectrum Disorder and Educational Achievement","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Prenatal Substance Exposure Effects","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Government of Alberta","funders":"","keywords":"Fetal Alcohol Spectrum Disorder; Birth certificate; Medicine; Test (biology); Psychology; Family medicine; Medical education; Pediatrics; Pregnancy; Environmental health","score_opus":0.0740782931437282,"score_gpt":0.41367052098951546,"score_spread":0.33959222784578724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891039173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9755108,0.00013723664,0.0064327763,0.011736296,0.004274751,0.0004649906,0.001067515,0.00002770115,0.00034794986],"genre_scores_gemma":[0.9870336,0.000029296083,0.006571958,0.00058737054,0.0020967785,0.0000051937236,0.0035036833,0.000013195397,0.00015890526],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975632,0.000028800194,0.00032910664,0.0006022582,0.0012467236,0.00022991837],"domain_scores_gemma":[0.9982266,0.00008646611,0.00020042408,0.0008831598,0.00036534294,0.00023800199],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012529462,0.00012851993,0.00012239616,0.00029994568,0.00040444406,0.00030065465,0.0017132714,0.000038307186,0.00011826833],"category_scores_gemma":[0.001005935,0.00010604296,0.000019387522,0.00022019292,0.00027731014,0.0035066402,0.0005726414,0.00017759719,0.000022453001],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028083464,0.0022395821,0.71992767,0.000046805493,0.00035533909,0.00004771411,0.0006630188,0.000098377735,0.026534515,0.045580648,0.016272364,0.18542561],"study_design_scores_gemma":[0.0020210529,0.00071752525,0.9161015,0.00014465774,0.000039521983,0.00043919776,0.00004320287,0.04034214,0.0006732682,0.0024897296,0.036768094,0.00022009034],"about_ca_topic_score_codex":0.00008823917,"about_ca_topic_score_gemma":0.0003705076,"teacher_disagreement_score":0.19617383,"about_ca_system_score_codex":0.0001613808,"about_ca_system_score_gemma":0.0002791954,"threshold_uncertainty_score":0.43243062},"labels":[],"label_agreement":null},{"id":"W2891047905","doi":"10.23889/ijpds.v3i4.597","title":"Linked data and inclusion health: Harmonised international data linkage to identify determinants of health inequalities","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"BC Centre for Disease Control; McMaster University","funders":"","keywords":"Health equity; Inclusion (mineral); Social determinants of health; Inequality; Equity (law); Social exclusion; Mental health; Commission; Psychology; Public relations; Political science; Economic growth; Social psychology; Health care; Economics; Psychiatry","score_opus":0.32628011253806255,"score_gpt":0.5508412371952067,"score_spread":0.22456112465714417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891047905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84158164,0.00072016206,0.0604119,0.068136394,0.010703442,0.0017975176,0.016271217,0.000090101836,0.00028760824],"genre_scores_gemma":[0.9758682,0.0003137062,0.012943391,0.0017694624,0.00090105284,0.0000030708634,0.008081363,0.000014299744,0.00010544025],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9961962,0.00006285367,0.0010276095,0.0007259333,0.0017010239,0.00028637404],"domain_scores_gemma":[0.9965397,0.00009108074,0.00078162405,0.0016285682,0.0006885382,0.00027046088],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0055380957,0.00013849555,0.000279664,0.0005874681,0.00088702294,0.00034506255,0.0053002816,0.000029662857,0.000077506396],"category_scores_gemma":[0.0021145006,0.00012666827,0.000022357623,0.00027790875,0.00028577168,0.0036386317,0.02027316,0.0001259778,0.0000054029265],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001311779,0.00079564535,0.13505867,0.0005932154,0.0003881118,0.000040432136,0.005390058,0.000053711014,0.0021036535,0.0044358745,0.0714896,0.77833927],"study_design_scores_gemma":[0.004371224,0.00073523604,0.5926039,0.0019514852,0.000080987535,0.00023368419,0.0015138868,0.28977707,0.000101813646,0.0041636936,0.104066834,0.00040017487],"about_ca_topic_score_codex":0.000747858,"about_ca_topic_score_gemma":0.00033938437,"teacher_disagreement_score":0.7779391,"about_ca_system_score_codex":0.0002737572,"about_ca_system_score_gemma":0.0009987693,"threshold_uncertainty_score":0.9876507},"labels":[],"label_agreement":null},{"id":"W2891049047","doi":"10.23889/ijpds.v3i4.841","title":"Evaluation of interventions to improve inpatient hospital documentation within electronic health records: A Systematic Review","year":2018,"lang":"en","type":"review","venue":"International Journal for Population Data Science","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Health Sciences Centre; University of Calgary","funders":"","keywords":"Documentation; Psychological intervention; CINAHL; Medicine; Data extraction; MEDLINE; Observational study; Grey literature; Cochrane Library; Checklist; Family medicine; Nursing; Meta-analysis; Psychology; Computer science","score_opus":0.2781425547446029,"score_gpt":0.6192595365496895,"score_spread":0.34111698180508654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891049047","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004141929,0.95392275,0.006034159,0.00079284864,0.01600469,0.021918362,0.001193154,0.000039821083,0.00005281152],"genre_scores_gemma":[0.00029940155,0.99102116,0.0015694096,0.0004864417,0.0010801762,0.0027632662,0.002439335,0.00006773484,0.00027308593],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9828308,0.003469355,0.0072462275,0.0010417093,0.0044234316,0.0009884731],"domain_scores_gemma":[0.9786254,0.0006287855,0.011642234,0.0014170328,0.00728069,0.00040584934],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.06488416,0.0004270471,0.0021032402,0.0013165489,0.0010223341,0.00014038279,0.0037251164,0.00018895116,0.00015069311],"category_scores_gemma":[0.01792653,0.00034323306,0.00046658082,0.0012574357,0.00009211218,0.0020009826,0.00065315526,0.0009427348,0.00013626984],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.000017172888,0.00017487933,0.000031058065,0.83023304,0.0003986129,3.797484e-7,0.0006073444,0.000007985916,4.05321e-7,0.0018182858,0.0089422995,0.15776852],"study_design_scores_gemma":[0.00062319945,0.0010438808,0.000019137371,0.9268686,0.002040646,0.000038325543,0.00022002228,0.0013353454,2.2594767e-7,0.00079137646,0.06663549,0.00038370813],"about_ca_topic_score_codex":0.0007281357,"about_ca_topic_score_gemma":0.0012024577,"teacher_disagreement_score":0.15738481,"about_ca_system_score_codex":0.010844649,"about_ca_system_score_gemma":0.016659686,"threshold_uncertainty_score":0.99990195},"labels":[],"label_agreement":null},{"id":"W2891080986","doi":"10.23889/ijpds.v3i4.630","title":"Patient Experiences with Cardiac Surgery in Alberta, Canada: Results from a Validated Survey","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Patient Satisfaction in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Angioplasty; Cardiac surgery; Percutaneous coronary intervention; Acute care; Emergency medicine; Intervention (counseling); Health care; Surgery; Internal medicine; Nursing","score_opus":0.18263470754848582,"score_gpt":0.4598707141966616,"score_spread":0.27723600664817577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891080986","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98074204,0.000010169652,0.00035221904,0.001190349,0.0124246925,0.00041978227,0.004748726,0.00001274579,0.00009928554],"genre_scores_gemma":[0.9945948,0.000009328018,0.00086145865,0.00040991907,0.0005026804,0.000051662086,0.0034963016,0.000011429622,0.000062381245],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9960016,0.00048643423,0.0011103981,0.0005380663,0.0014234295,0.00044008845],"domain_scores_gemma":[0.99391377,0.0027483553,0.00086416956,0.0005019842,0.0017572334,0.00021449626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027642692,0.00013120151,0.00022747593,0.0003372394,0.0009902646,0.00007428868,0.0009056113,0.00006164272,0.00012368405],"category_scores_gemma":[0.006635738,0.00010650046,0.000021921012,0.0005818021,0.00016399712,0.0016722298,0.00023074805,0.00029328043,0.000013087775],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047816942,0.000010087771,0.9823332,0.000002401368,0.000013987448,0.0000032107523,0.0037591571,0.000033801545,0.000010725278,0.00003090281,0.0113754105,0.0019489841],"study_design_scores_gemma":[0.0003585615,0.00004498666,0.98722374,0.00020752595,0.0000033757585,0.0000031365394,0.0037148318,0.0021497563,0.000059553437,0.000051406278,0.0060377703,0.00014533842],"about_ca_topic_score_codex":0.95418185,"about_ca_topic_score_gemma":0.9603471,"teacher_disagreement_score":0.013852809,"about_ca_system_score_codex":0.0010498635,"about_ca_system_score_gemma":0.003911788,"threshold_uncertainty_score":0.7944077},"labels":[],"label_agreement":null},{"id":"W2891082052","doi":"10.23889/ijpds.v3i4.782","title":"Using family physician Electronic Medical Record data to measure the pathways of cancer care","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Breast cancer; Lung cancer; Specialty; Cancer; Medical record; Internal medicine; Disease; Oncology; Family medicine; Intensive care medicine","score_opus":0.17940420178435806,"score_gpt":0.44479775088113793,"score_spread":0.26539354909677987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891082052","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93877023,0.0008965972,0.05475989,0.0016992554,0.0027714584,0.00015337853,0.000847163,0.0000074383483,0.000094570525],"genre_scores_gemma":[0.99223906,0.000085365435,0.0050494773,0.00095032336,0.0013398485,0.0000022334066,0.0003183892,0.0000055379655,0.0000097409675],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985561,0.000026450685,0.00021634177,0.0002977436,0.0007188093,0.00018455693],"domain_scores_gemma":[0.99864334,0.000018528584,0.00014753635,0.0005287784,0.0005841529,0.00007764487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094757346,0.000063659456,0.00007081046,0.000056273464,0.00022233285,0.000060125854,0.0031771967,0.000049844697,0.000007393668],"category_scores_gemma":[0.001042943,0.000043226468,0.000023123583,0.00014780523,0.0002780865,0.00003747624,0.0007699936,0.00009111271,0.0000010300281],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001717135,0.00003668821,0.006825464,0.0000056944477,0.00008554151,0.0000011835813,0.00015766063,0.000064000094,0.22472738,0.0004024094,0.0068063475,0.7607159],"study_design_scores_gemma":[0.0016608294,0.0010556589,0.06451881,0.0004707325,0.000107444284,0.00009454684,0.001983345,0.07050005,0.027658917,0.0012462741,0.83008754,0.0006158366],"about_ca_topic_score_codex":0.00023225335,"about_ca_topic_score_gemma":0.00067331136,"teacher_disagreement_score":0.8232812,"about_ca_system_score_codex":0.000047757658,"about_ca_system_score_gemma":0.00062240707,"threshold_uncertainty_score":0.5904075},"labels":[],"label_agreement":null},{"id":"W2891086908","doi":"10.23889/ijpds.v3i4.687","title":"Using routinely collected laboratory and health administrative data to assess influenza vaccine effectiveness: introducing the Flu and Other Respiratory Viruses Research (FOREVER) Cohort","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Memorial University of Newfoundland; Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto; SickKids Foundation; Public Health Ontario; William Osler Health System; University of Ottawa; Institute for Clinical Evaluative Sciences; Children's Hospital of Eastern Ontario; St. Joseph’s Healthcare Hamilton; Hospital for Sick Children","funders":"","keywords":"Medicine; Influenza vaccine; Cohort; Cohort study; Public health; Vaccine efficacy; Vaccination; Respiratory illness; Family medicine; Immunology; Respiratory system; Internal medicine; Pathology","score_opus":0.7572691283770886,"score_gpt":0.6436568816891202,"score_spread":0.11361224668796843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891086908","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99270815,0.00045903068,0.0023371878,0.0015235511,0.0005134365,0.0013463061,0.0010510223,0.000018857703,0.000042454678],"genre_scores_gemma":[0.97917175,0.00004029244,0.010084356,0.009008484,0.0015739655,0.000030861796,0.000048335238,0.000028963279,0.000013013798],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99647814,0.00037026664,0.0005216768,0.00068870094,0.001534643,0.0004065625],"domain_scores_gemma":[0.99478155,0.0006391555,0.00025276642,0.0008374625,0.0032216862,0.00026739598],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.01717383,0.00013977454,0.00024956127,0.00058306736,0.00170919,0.00053906976,0.0013039652,0.00003729352,0.00001604789],"category_scores_gemma":[0.012180453,0.00009796796,0.000013047187,0.0010234363,0.0005978988,0.0016294683,0.0016744283,0.00036871183,0.0000032846476],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014906805,0.00007138302,0.9694885,0.000049346574,0.00022196597,0.000007974823,0.000600567,0.00004139375,0.017767932,0.0009528879,0.0066212798,0.0026860654],"study_design_scores_gemma":[0.001294278,0.00059836905,0.9287604,0.00037127238,0.0000262731,0.00008203483,0.0003620887,0.007934397,0.0010794455,0.00014803722,0.05921515,0.00012822862],"about_ca_topic_score_codex":0.00066723186,"about_ca_topic_score_gemma":0.00052168744,"teacher_disagreement_score":0.052593872,"about_ca_system_score_codex":0.00050388096,"about_ca_system_score_gemma":0.0015715294,"threshold_uncertainty_score":0.99959046},"labels":[],"label_agreement":null},{"id":"W2891094870","doi":"10.23889/ijpds.v3i4.970","title":"In-Utero SSRI and SNRI Exposure and the Risk of Neurodevelopmental Disorders in Children: A Population-Based Retrospective Cohort Study Utilizing Linked Administrative Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal Mental Health During Pregnancy and Postpartum","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Hazard ratio; Medicine; Autism spectrum disorder; Population; Mood; Cohort; Attention deficit hyperactivity disorder; Anxiety; Psychiatry; Pediatrics; Proportional hazards model; Cohort study; Retrospective cohort study; Offspring; Pregnancy; Internal medicine; Autism; Confidence interval","score_opus":0.043578930409814275,"score_gpt":0.3870830920533932,"score_spread":0.34350416164357894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891094870","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99726605,0.000049812803,0.00012064722,0.00064597203,0.00052276463,0.0010433971,0.00032607,0.0000043515665,0.000020907086],"genre_scores_gemma":[0.998457,0.00009146062,0.0009722201,0.000111046626,0.000096659765,0.000011913289,0.0002453981,0.0000058411415,0.000008429656],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982767,0.00009783692,0.000511235,0.00039852477,0.00056838914,0.00014732585],"domain_scores_gemma":[0.9989826,0.00012744148,0.000345352,0.00034439677,0.0001329373,0.00006724055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021233251,0.000099254765,0.00019013569,0.00023626904,0.00022508098,0.000078982725,0.00058175495,0.000025091194,0.000010299389],"category_scores_gemma":[0.00073722895,0.00007227302,0.0000130622475,0.00019677368,0.00025908294,0.0009776155,0.00029627336,0.00019696548,2.7404678e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006974931,0.00011144695,0.9978098,0.000013831352,0.000025770489,0.0000025846143,0.00036031546,0.0000066683338,0.0000052345695,0.00018551499,0.0000035840121,0.00077771244],"study_design_scores_gemma":[0.0030987714,0.000267131,0.9852853,0.00030143964,0.000024623987,0.000077539364,0.00015090739,0.010209244,0.0000128759475,0.00050171465,0.000006445128,0.00006401331],"about_ca_topic_score_codex":0.001809572,"about_ca_topic_score_gemma":0.0019172241,"teacher_disagreement_score":0.01252455,"about_ca_system_score_codex":0.00010165413,"about_ca_system_score_gemma":0.000115602386,"threshold_uncertainty_score":0.2947208},"labels":[],"label_agreement":null},{"id":"W2891102177","doi":"10.23889/ijpds.v3i4.670","title":"Calgary Thrives: Data sharing and linkage in the not-for-profit sector.","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Mount Royal University","funders":"","keywords":"Business; Agency (philosophy); Linkage (software); Data sharing; Context (archaeology); Non profit; Public relations; Marketing; Political science; Medicine","score_opus":0.3804431858611188,"score_gpt":0.5653982289884611,"score_spread":0.18495504312734234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891102177","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89879495,0.00026453225,0.033302635,0.047169093,0.013064746,0.0020950057,0.0026534142,0.000054979602,0.0026006685],"genre_scores_gemma":[0.96316904,0.00019210568,0.01185789,0.019306727,0.0033664496,0.000039847993,0.0017168468,0.000016686492,0.00033439658],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979659,0.00007265872,0.0005585505,0.00046570064,0.0005948646,0.00034235473],"domain_scores_gemma":[0.997763,0.0005560984,0.00029906866,0.0008568753,0.00043598533,0.00008898871],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0062069306,0.000087002816,0.0001231059,0.00023014487,0.0014128897,0.00016668421,0.004419342,0.000058847138,0.00006847635],"category_scores_gemma":[0.001825056,0.000060471477,0.000017646356,0.00019539478,0.00015618146,0.002546714,0.0014598056,0.0003506637,0.000011153049],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015490066,0.0000095547475,0.9342042,0.000052236264,0.000015592628,0.000003972875,0.0016876422,0.000003021945,0.00020351303,0.022207761,0.024726791,0.0167308],"study_design_scores_gemma":[0.0010371804,0.000061277664,0.8943594,0.00013519301,0.000012803149,0.00003217611,0.00064055144,0.04033408,0.0000066217312,0.0076086232,0.055636883,0.00013520218],"about_ca_topic_score_codex":0.00060429587,"about_ca_topic_score_gemma":0.0015260286,"teacher_disagreement_score":0.06437413,"about_ca_system_score_codex":0.00022729937,"about_ca_system_score_gemma":0.0006377703,"threshold_uncertainty_score":0.9998871},"labels":[],"label_agreement":null},{"id":"W2891130282","doi":"10.23889/ijpds.v3i4.948","title":"BC Data ScoutTM: A New Tool To Investigate Datasets For Health Research","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; Ministry of Health","funders":"","keywords":"Computer science; Data quality; Data science; Sophistication; Benchmarking; Population; Service (business); World Wide Web; Database; Medicine; Business","score_opus":0.43599800066950667,"score_gpt":0.5798542166762604,"score_spread":0.1438562160067537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891130282","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27566653,0.0008003431,0.458575,0.19120899,0.021861438,0.007415174,0.044166885,0.00014315508,0.00016246852],"genre_scores_gemma":[0.42887875,0.00043606607,0.4771793,0.017040014,0.018945567,0.00004513868,0.056124154,0.00008214384,0.0012688817],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961199,0.00005480393,0.00056984485,0.00070030027,0.0020049433,0.00055020704],"domain_scores_gemma":[0.99581116,0.00014208317,0.00018331694,0.0016372551,0.0012819517,0.0009442463],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.009737952,0.000106780164,0.0002129657,0.0006416071,0.0008526153,0.00037580074,0.0027772326,0.00004021149,0.000040862342],"category_scores_gemma":[0.008663594,0.00008723943,0.000053320455,0.0006001246,0.00023068389,0.0019626436,0.0010231754,0.00023590114,0.000047135767],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064497464,0.00006347132,0.007800941,0.00004213413,0.00007898914,0.000006462697,0.00018534686,0.000028458311,0.0003779153,0.0017956313,0.82105094,0.16792475],"study_design_scores_gemma":[0.0015827884,0.00042341326,0.051121496,0.0002469131,0.000023980598,0.0002838916,0.00005221764,0.014525547,0.000114360235,0.0016461149,0.9298463,0.00013296011],"about_ca_topic_score_codex":0.002007113,"about_ca_topic_score_gemma":0.000630956,"teacher_disagreement_score":0.17416897,"about_ca_system_score_codex":0.00036819806,"about_ca_system_score_gemma":0.0033125551,"threshold_uncertainty_score":0.99968684},"labels":[],"label_agreement":null},{"id":"W2891132287","doi":"10.23889/ijpds.v3i4.975","title":"Use of the CANHEART ‘big data’ registry to conduct a large randomized registry clinical trial to improve lipid management in Ontario, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University Health Network; Women's College Hospital; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Randomized controlled trial; Population; Cohort; Clinical trial; Medical prescription; Statin; Family medicine; Record linkage; Emergency medicine; Myocardial infarction; Physical therapy; Environmental health; Internal medicine","score_opus":0.3171817569459236,"score_gpt":0.4689480271991361,"score_spread":0.1517662702532125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891132287","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95946366,0.000008155362,0.0032510194,0.011488356,0.020150522,0.0032687723,0.0013015682,0.000011566491,0.0010563738],"genre_scores_gemma":[0.98940235,0.000008350655,0.004032792,0.0019291105,0.0014038346,0.00002522704,0.0005072112,0.000009949531,0.002681174],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.996822,0.000078814184,0.0009616255,0.00054619485,0.0013261313,0.00026522475],"domain_scores_gemma":[0.99718744,0.00017251718,0.0004449352,0.0015530183,0.00042725896,0.00021482098],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037047595,0.00011693043,0.00031626198,0.00020003671,0.00014518178,0.00022760524,0.0023973898,0.000029448107,0.000093477494],"category_scores_gemma":[0.0046458496,0.000084866,0.00007057196,0.00030402147,0.00022055033,0.00081049977,0.0015639309,0.00019915326,0.000002483478],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.3760331,0.0009489077,0.05018715,0.00008566731,0.00084858533,0.0001265962,0.0002535873,0.0003670734,0.00024663453,0.013022976,0.5323079,0.02557183],"study_design_scores_gemma":[0.24346074,0.0002990322,0.17119463,0.0005075528,0.00027174546,0.000050004313,0.0003062521,0.009444659,0.000039298502,0.00037169724,0.5737704,0.00028399163],"about_ca_topic_score_codex":0.56679827,"about_ca_topic_score_gemma":0.90694964,"teacher_disagreement_score":0.34015137,"about_ca_system_score_codex":0.0007847149,"about_ca_system_score_gemma":0.0028710507,"threshold_uncertainty_score":0.5561852},"labels":[],"label_agreement":null},{"id":"W2891132725","doi":"10.23889/ijpds.v3i4.1033","title":"Development and Characteristics of the Provincial Overdose Cohort in British Columbia, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ministry of Health; Provincial Health Services Authority; BC Centre for Disease Control","funders":"","keywords":"Opioid overdose; Medicine; Coroner; Medical emergency; Emergency medicine; Drug overdose; Cohort; Emergency department; Psychological intervention; Medical prescription; Population; Public health; Polysubstance dependence; Poison control; Family medicine; Suicide prevention; Environmental health; Opioid; Substance abuse; Psychiatry; (+)-Naloxone; Nursing","score_opus":0.019825170659816573,"score_gpt":0.3052223206039213,"score_spread":0.2853971499441047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891132725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99815273,0.000009454538,0.000047476038,0.00027354428,0.0010213583,0.00023384072,0.00023196796,0.0000017749031,0.000027870568],"genre_scores_gemma":[0.9972222,0.000008491331,0.0022696508,0.00013969679,0.000121480756,0.0000036589397,0.00011743843,0.0000033862193,0.00011404094],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99886346,0.0000064342476,0.0002793867,0.00014971,0.00060594897,0.00009504232],"domain_scores_gemma":[0.99928147,0.00001423711,0.00015888707,0.0001410593,0.0003548702,0.000049468166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003405505,0.00003373688,0.00007972466,0.000039185034,0.00015273756,0.00012971442,0.0003661574,0.000012855151,0.000017390665],"category_scores_gemma":[0.00043814137,0.000036124326,0.000008823471,0.000108975146,0.00010380835,0.00028103322,0.00016885501,0.000050983013,1.9105524e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013191109,0.000040063664,0.9775039,0.0000047700914,0.0000119225615,0.0000049665764,0.000068755005,3.050861e-7,0.00009591316,0.00002174587,0.00031211347,0.02192238],"study_design_scores_gemma":[0.0004292147,0.000019646472,0.9940232,0.00009624855,0.000009098949,0.000097119046,0.00005183333,0.00070603634,0.00007042718,0.000035086712,0.0044262493,0.000035813377],"about_ca_topic_score_codex":0.44012678,"about_ca_topic_score_gemma":0.91849935,"teacher_disagreement_score":0.4783726,"about_ca_system_score_codex":0.00033959586,"about_ca_system_score_gemma":0.0016535353,"threshold_uncertainty_score":0.5636015},"labels":[],"label_agreement":null},{"id":"W2891156194","doi":"10.23889/ijpds.v3i4.675","title":"Governance Challenges to Promoting Data Readiness and Data Linkage for Not-for-Profit Organizational Service Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; Alberta Health Services","funders":"","keywords":"Business; Data governance; Public relations; Corporate governance; Data sharing; Information governance; Service (business); Internet privacy; Political science; Marketing; Information system; Data quality; Law","score_opus":0.5205717022128199,"score_gpt":0.5341023824725832,"score_spread":0.013530680259763339,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891156194","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018094022,0.00014716465,0.7422874,0.09195503,0.0063521555,0.0016695275,0.13932045,0.000053529846,0.00012072865],"genre_scores_gemma":[0.5442293,0.00039101663,0.35924354,0.0066046435,0.0067539886,0.000041911768,0.081634976,0.00006880587,0.0010317566],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9935308,0.00007230905,0.0010699073,0.0022292603,0.0027075382,0.00039018155],"domain_scores_gemma":[0.9879971,0.0012418905,0.00092732674,0.0063342624,0.0032645378,0.00023485387],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.022004062,0.00019285557,0.00025007885,0.0003024803,0.0010000524,0.0030130874,0.032738637,0.000056758203,0.000051349423],"category_scores_gemma":[0.039858814,0.00016297176,0.000016801216,0.0007857283,0.00020039905,0.019910464,0.019166233,0.00011464035,0.000032027514],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067446317,0.00013316495,0.009570045,0.00015132257,0.00020693465,0.000005488898,0.0011567497,0.00014254704,0.001436921,0.19675414,0.24009693,0.5496713],"study_design_scores_gemma":[0.0009955085,0.000097297,0.045754973,0.00015505607,0.000051464893,0.00005715485,0.00046810744,0.52161115,0.000097752265,0.017896073,0.41243985,0.00037558918],"about_ca_topic_score_codex":0.00012720465,"about_ca_topic_score_gemma":0.0017155508,"teacher_disagreement_score":0.5492957,"about_ca_system_score_codex":0.00008230914,"about_ca_system_score_gemma":0.00033548023,"threshold_uncertainty_score":0.9980219},"labels":[],"label_agreement":null},{"id":"W2891203968","doi":"10.23889/ijpds.v3i4.599","title":"Linking cohort data with administrative health data to develop a new hypertension prediction model to aid precision health approach","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Cohort; Logistic regression; Population; Disease; Medical record; Health care; Environmental health; Cohort study; Population health; Family medicine; Medical emergency; Internal medicine","score_opus":0.2579713076364722,"score_gpt":0.43027467586462254,"score_spread":0.17230336822815034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891203968","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06534911,0.00001376555,0.92012614,0.009786858,0.00072267925,0.0014639735,0.0023219245,0.00003967037,0.00017585426],"genre_scores_gemma":[0.5030085,0.00005165196,0.48533106,0.00544518,0.00050333445,0.000011650008,0.0055218264,0.0000255663,0.00010125597],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99419564,0.00011726348,0.00083133,0.0019104949,0.002347756,0.00059751363],"domain_scores_gemma":[0.99605864,0.00009306197,0.000560018,0.002121148,0.00023422457,0.0009328751],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0075834324,0.00022222544,0.00024437663,0.00027127183,0.0012189702,0.00039798333,0.005442972,0.00004640275,0.00004837331],"category_scores_gemma":[0.0017456112,0.00019024093,0.000012307249,0.0009369879,0.00020049428,0.005842372,0.004352217,0.00027357024,0.00007083613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009346851,0.0005233309,0.17827421,0.000025503025,0.00008412758,0.000009200461,0.0030445394,0.05936801,0.0021621878,0.00029439805,0.09224378,0.663036],"study_design_scores_gemma":[0.00061512896,0.0005060583,0.20153734,0.00024846155,0.00001277686,0.00020786232,0.00016600794,0.7663729,0.000046528683,0.00024704324,0.029772198,0.00026768178],"about_ca_topic_score_codex":0.0013076005,"about_ca_topic_score_gemma":0.001473622,"teacher_disagreement_score":0.7070049,"about_ca_system_score_codex":0.0011848179,"about_ca_system_score_gemma":0.0014902041,"threshold_uncertainty_score":0.9999381},"labels":[],"label_agreement":null},{"id":"W2891248192","doi":"10.23889/ijpds.v3i4.832","title":"Identification of Frailty using EMR and Admin data: A complex issue","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Frailty in Older Adults","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; University of Manitoba; University of British Columbia; Manitoba Health","funders":"","keywords":"Audit; Medical record; Vulnerability (computing); Medicine; Population; Gerontology; Medical emergency; Computer science; Computer security; Environmental health; Business","score_opus":0.270249451982674,"score_gpt":0.49405528028748724,"score_spread":0.22380582830481321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891248192","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9208317,0.000057596942,0.07071178,0.0035360495,0.0027943915,0.00036310134,0.0015963404,0.000019608828,0.00008943795],"genre_scores_gemma":[0.9715199,0.00001785141,0.026312236,0.00016677189,0.00087143393,8.0716836e-7,0.00093670294,0.0000075552753,0.00016677781],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981592,0.000016260581,0.0005132036,0.00035690243,0.0008200558,0.00013436472],"domain_scores_gemma":[0.9976568,0.000055733843,0.00040504555,0.00069797115,0.001074333,0.000110095134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012797451,0.00007408821,0.00012378418,0.00027947337,0.00021729413,0.00016727019,0.0012992658,0.000029077793,0.00009550891],"category_scores_gemma":[0.0020137648,0.00006731448,0.0000165312,0.00022822667,0.00037895792,0.0024033976,0.0005283138,0.00008256823,0.000006814476],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007410136,0.00043862124,0.18104513,0.00012155808,0.00024963423,0.000018443952,0.0010099277,0.00014243145,0.61388427,0.0034762057,0.033159487,0.16571328],"study_design_scores_gemma":[0.001303198,0.00014286407,0.42146093,0.00019924864,0.00007430817,0.00083675265,0.00013785754,0.5455957,0.003949949,0.00096142135,0.025199052,0.00013870561],"about_ca_topic_score_codex":0.00019787492,"about_ca_topic_score_gemma":0.0000736313,"teacher_disagreement_score":0.60993433,"about_ca_system_score_codex":0.00008601201,"about_ca_system_score_gemma":0.00017541918,"threshold_uncertainty_score":0.2745005},"labels":[],"label_agreement":null},{"id":"W2891262184","doi":"10.23889/ijpds.v3i4.661","title":"Validating Self-reported Chronic Conditions in Alberta’s Tomorrow Project Cohort: Data Linkage to Administrative Healthcare Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; Alberta Health; University of Alberta","funders":"","keywords":"Medicine; Cohort; Cirrhosis; Diabetes mellitus; Cancer; Chronic liver disease; Colorectal cancer; Health care; Disease; Internal medicine; Ulcerative colitis; Cohort study","score_opus":0.2802972221484328,"score_gpt":0.532508406516352,"score_spread":0.25221118436791923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891262184","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86792606,0.00017919006,0.016729264,0.06416478,0.010529787,0.00818958,0.025936708,0.00031475475,0.0060298746],"genre_scores_gemma":[0.9538175,0.000040098952,0.008924707,0.0006125344,0.0013364906,0.000025705924,0.03496542,0.000018916922,0.00025861207],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99636424,0.000054909233,0.0008262529,0.0010767635,0.0012793965,0.00039842058],"domain_scores_gemma":[0.9959671,0.00014243608,0.00048031737,0.0024120584,0.0007539937,0.0002441255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002284032,0.00017720829,0.00022254727,0.0005979524,0.0004040441,0.000547662,0.0041275285,0.000044867833,0.00017237278],"category_scores_gemma":[0.0030367563,0.00016727191,0.00002646109,0.0007451654,0.00019718935,0.004558063,0.0022461826,0.00022818668,0.000028375678],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014391999,0.002519261,0.6466381,0.0005959496,0.002737867,0.0009143593,0.0026876773,0.0005695973,0.0031801804,0.0383218,0.2697085,0.030687492],"study_design_scores_gemma":[0.004846578,0.0010585611,0.4847555,0.0017099718,0.00065844686,0.0011424291,0.0016905438,0.42200255,0.00024485422,0.0016512346,0.0794145,0.00082484464],"about_ca_topic_score_codex":0.004878511,"about_ca_topic_score_gemma":0.013651006,"teacher_disagreement_score":0.42143294,"about_ca_system_score_codex":0.00083638576,"about_ca_system_score_gemma":0.0031551975,"threshold_uncertainty_score":0.7670044},"labels":[],"label_agreement":null},{"id":"W2891263329","doi":"10.23889/ijpds.v3i4.656","title":"Impact of clinical subtypes of preterm birth on child health and development","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Preterm Birth and Chorioamnionitis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; University of Calgary","funders":"","keywords":"Medicine; Gestational age; Gestation; Confounding; Odds ratio; Pediatrics; Premature birth; Obstetrics; Logistic regression; Pregnancy; Odds; Internal medicine","score_opus":0.12270367150827514,"score_gpt":0.48851608618524445,"score_spread":0.3658124146769693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891263329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973343,0.000049526963,0.0010740774,0.00034997595,0.0007352533,0.00012027641,0.0001672166,0.0000044198,0.00016492663],"genre_scores_gemma":[0.9940327,0.00010324729,0.0052524903,0.00014394533,0.00032165766,6.150095e-7,0.0001250514,0.0000036388776,0.000016673994],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986094,0.000017750472,0.000563331,0.00017932904,0.00051723165,0.00011295674],"domain_scores_gemma":[0.9986525,0.000049709783,0.0004530764,0.0001920934,0.00046382943,0.00018875785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010485579,0.000056421326,0.00016234446,0.00019804396,0.00012034974,0.000028413944,0.00037653913,0.00002214812,0.000031542295],"category_scores_gemma":[0.0008203687,0.000040957806,0.000040447117,0.0000867922,0.00021285997,0.00039000472,0.00009793157,0.00008561053,0.0000012413835],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005734611,0.00007153903,0.8395457,0.000012531213,0.000045481454,8.4839144e-7,0.00014609327,0.0000020383068,0.000057444897,0.00027678657,0.00027927148,0.15898876],"study_design_scores_gemma":[0.00087450596,0.0011541345,0.99358845,0.00021751823,0.0000037431419,0.000100092315,0.000013653755,0.0013764664,0.00018328104,0.000092390546,0.0023552242,0.000040526556],"about_ca_topic_score_codex":0.000049371294,"about_ca_topic_score_gemma":0.00001562234,"teacher_disagreement_score":0.15894823,"about_ca_system_score_codex":0.000057050962,"about_ca_system_score_gemma":0.0006492951,"threshold_uncertainty_score":0.16702108},"labels":[],"label_agreement":null},{"id":"W2891264182","doi":"10.23889/ijpds.v3i4.823","title":"A Bayesian Network Model of the Relationships between Chronic Disease Indicators","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Bayesian network; Context (archaeology); Bayesian probability; Computer science; Causality (physics); Econometrics; Bayes' theorem; Health informatics; Graphical model; Data mining; Machine learning; Data science; Public health; Artificial intelligence; Medicine; Mathematics; Geography","score_opus":0.08500453241448185,"score_gpt":0.3795234618158437,"score_spread":0.2945189294013618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891264182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6855288,0.00016014773,0.30994365,0.001954611,0.0017059727,0.00015744068,0.0004336825,0.000009233909,0.0001064674],"genre_scores_gemma":[0.9916383,0.000013561585,0.006770231,0.000062020226,0.0012442493,0.0000020965888,0.0001748625,0.0000044083718,0.00009025513],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99900323,0.00003239734,0.0002317735,0.00020178637,0.00039254467,0.00013826042],"domain_scores_gemma":[0.9991103,0.000025497335,0.00022177551,0.0003543321,0.00019228131,0.00009583048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091226626,0.00005487472,0.00005421121,0.00007068314,0.00038910413,0.00004834604,0.001529722,0.00004612796,0.000005333624],"category_scores_gemma":[0.0012582894,0.00003839872,0.000040880503,0.00018837358,0.0004831952,0.000031138232,0.00038519295,0.00009405611,8.294208e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012681409,0.000045988763,0.91675085,0.000008719654,0.00008960891,4.3382065e-7,0.00008364375,0.00792342,0.0060572564,0.0039532688,0.01086457,0.054095455],"study_design_scores_gemma":[0.0006270833,0.00016588488,0.757274,0.000109110726,0.000053365045,0.000012432321,0.00003275682,0.19540891,0.0018874775,0.013466773,0.030748377,0.00021382884],"about_ca_topic_score_codex":0.0000060348248,"about_ca_topic_score_gemma":0.000028316854,"teacher_disagreement_score":0.30610952,"about_ca_system_score_codex":0.000035005556,"about_ca_system_score_gemma":0.0003477075,"threshold_uncertainty_score":0.29927135},"labels":[],"label_agreement":null},{"id":"W2891267781","doi":"10.23889/ijpds.v3i4.922","title":"Mapping Clinical Contents onto Longitudinal Depictions of Cross-Continuum Service Events in Island Health: Clinical Context Coding Scheme","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Island Health; University of British Columbia","funders":"","keywords":"Computer science; Coding (social sciences); Software deployment; Data science; Image stitching; Service (business); Context (archaeology); Software engineering; Artificial intelligence; Business; Geography; Marketing; Mathematics","score_opus":0.32611995888242495,"score_gpt":0.5149831215027734,"score_spread":0.1888631626203484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891267781","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9751522,0.00003373314,0.011094193,0.0044708108,0.008664256,0.00034319138,0.00007077051,0.000027958058,0.00014287083],"genre_scores_gemma":[0.9946017,0.000019643785,0.0012368308,0.0014202293,0.0025526693,0.000005338273,0.000112551235,0.000009846088,0.000041190462],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967063,0.000039982813,0.0018447613,0.000469635,0.0006065425,0.0003327908],"domain_scores_gemma":[0.99594927,0.00014157774,0.0013714783,0.00036142636,0.0021258097,0.00005043843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065253144,0.00011563469,0.0003368566,0.00059581053,0.00041896175,0.00023146064,0.0015432924,0.00010117455,0.00003658667],"category_scores_gemma":[0.0030308934,0.0001077869,0.000081365346,0.00058843737,0.00025318787,0.0035343447,0.0005263496,0.00029100425,0.000026367316],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000067769506,0.000091515045,0.9775788,0.000026215721,0.000023163208,0.00000209887,0.000022322007,0.00000223423,0.00003831187,0.0060413764,0.0007138855,0.015392286],"study_design_scores_gemma":[0.0014082281,0.000043847424,0.9552908,0.00031675337,0.0000037636978,0.000030368568,0.00014881532,0.016783096,0.0000030677597,0.0014376825,0.02443073,0.00010283526],"about_ca_topic_score_codex":0.008134077,"about_ca_topic_score_gemma":0.036042493,"teacher_disagreement_score":0.027908415,"about_ca_system_score_codex":0.0001251926,"about_ca_system_score_gemma":0.00018235733,"threshold_uncertainty_score":0.99847084},"labels":[],"label_agreement":null},{"id":"W2891278567","doi":"10.23889/ijpds.v3i4.1023","title":"A bayesian way to correct for measurement error in drug risk estimates from EHR data.","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"","keywords":"Confounding; Medicine; Statistics; Bayesian probability; Medical prescription; Medical record; Econometrics; Data mining; Computer science; Mathematics; Internal medicine; Pharmacology","score_opus":0.7320061462199375,"score_gpt":0.6324739632224308,"score_spread":0.09953218299750677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891278567","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020094061,0.000010168621,0.9643582,0.0012141077,0.006755008,0.0007148955,0.0067813345,0.000026501928,0.000045700475],"genre_scores_gemma":[0.26689577,0.0000041436915,0.7316582,0.00016074535,0.0010772499,0.000020433585,0.0001499574,0.00001544281,0.00001803782],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961194,0.00016507535,0.0011180544,0.00073125685,0.001544661,0.00032156557],"domain_scores_gemma":[0.985591,0.010984146,0.00067391095,0.001134944,0.0013719854,0.00024404789],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01653013,0.00015196549,0.0003066277,0.0002824825,0.00031355425,0.00039597822,0.0040493994,0.000047588317,0.0001228846],"category_scores_gemma":[0.28499994,0.00012764345,0.00004965151,0.0002961412,0.00018025356,0.0012015858,0.00081625656,0.0001819575,0.000016537537],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038179562,0.0013510081,0.0939034,0.000074930475,0.00054446916,0.00002256902,0.0014689829,0.00076154753,0.0036194136,0.059627432,0.19586194,0.63894635],"study_design_scores_gemma":[0.0011426313,0.00010864686,0.016473198,0.0002286664,0.000067782195,0.00000798947,0.000051142026,0.19083019,0.0004926678,0.78663737,0.0037571867,0.00020254505],"about_ca_topic_score_codex":0.00063900655,"about_ca_topic_score_gemma":0.0020023158,"teacher_disagreement_score":0.72700995,"about_ca_system_score_codex":0.00029364237,"about_ca_system_score_gemma":0.00017097585,"threshold_uncertainty_score":0.7524859},"labels":[],"label_agreement":null},{"id":"W2891312812","doi":"10.23889/ijpds.v3i4.1004","title":"Use of linked electronic health records to evaluate cardiovascular risk prediction models in Ontario, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Promotion and Cardiovascular Prevention","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Cohort; Medical record; Record linkage; Framingham Risk Score; Blood pressure; Cohort study; Database; Myocardial infarction; Framingham Heart Study; Demography; Family medicine; Emergency medicine; Gerontology; Medical emergency; Internal medicine; Environmental health; Disease; Population; Computer science","score_opus":0.11743077863760136,"score_gpt":0.3909245163310187,"score_spread":0.27349373769341734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891312812","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7797583,0.000091482776,0.21563016,0.0009733417,0.002509979,0.00078303687,0.00020073533,0.000011898415,0.00004106499],"genre_scores_gemma":[0.9932343,0.00017046175,0.0054916353,0.0002895874,0.00030734463,0.00000836804,0.0003486805,0.000009163639,0.00014049507],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99677974,0.0002428816,0.0006940155,0.0003620271,0.0016127179,0.00030861693],"domain_scores_gemma":[0.9977622,0.000029420704,0.00027552294,0.00050978444,0.0011937864,0.00022929549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0093952175,0.00008884629,0.00025035042,0.00039854788,0.00020363505,0.000057107784,0.00042840498,0.000037332728,0.000047706868],"category_scores_gemma":[0.000899971,0.00008439741,0.00012445869,0.00036315262,0.000044789762,0.0012448755,0.000105003215,0.0002665301,0.0000016930002],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005812757,0.00032142902,0.33355716,0.000077818164,0.0010760989,0.000011282387,0.0011670837,0.07916344,0.00025532028,0.0011225212,0.0061213607,0.57654524],"study_design_scores_gemma":[0.0012197109,0.0003709253,0.85489017,0.00022934219,0.00006459831,0.00012739707,0.000031697884,0.108011484,0.000035792527,0.00071833906,0.03421174,0.000088812645],"about_ca_topic_score_codex":0.8495478,"about_ca_topic_score_gemma":0.905615,"teacher_disagreement_score":0.5764564,"about_ca_system_score_codex":0.0029582724,"about_ca_system_score_gemma":0.0057773,"threshold_uncertainty_score":0.99985904},"labels":[],"label_agreement":null},{"id":"W2891313201","doi":"10.23889/ijpds.v3i4.836","title":"Secure data analysis environments: can we agree on criteria for “Appropriate secure access” to linked health data?","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of British Columbia","funders":"Economic and Social Research Council; Medical Research Council","keywords":"Custodians; Data governance; Computer science; Data quality; Data sharing; Cloud computing; Data access; Data integrity; Computer security; Authentication (law); Data warehouse; Data security; Information governance; Access control; Data science; Database; Business; Encryption; Service (business); Engineering; Information system; Medicine","score_opus":0.7073983465711722,"score_gpt":0.6730252174331381,"score_spread":0.03437312913803403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891313201","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060193364,0.0001170977,0.51089656,0.3615559,0.0074992552,0.0031425157,0.05634974,0.00006347566,0.00018208647],"genre_scores_gemma":[0.85810864,0.0005755476,0.09349147,0.0103043085,0.0042851553,0.000023759401,0.032376245,0.000040904095,0.0007939766],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9940289,0.00008747905,0.00096997916,0.0013934728,0.0030283162,0.00049181294],"domain_scores_gemma":[0.9929607,0.001148202,0.0005641065,0.003676037,0.0010302474,0.0006207101],"candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.012865317,0.00017545106,0.00034729435,0.0008002874,0.0006616822,0.0008353049,0.010880883,0.00012707495,0.00021335878],"category_scores_gemma":[0.023415474,0.00014450545,0.00007183229,0.00087203877,0.00034533383,0.0026040536,0.004580701,0.0007097347,0.000024387506],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009881526,0.0031728048,0.12247421,0.00060193264,0.005532159,0.0000859664,0.0032069487,0.0019041267,0.00645452,0.04386365,0.37414825,0.4286739],"study_design_scores_gemma":[0.0036763072,0.0019210356,0.16728586,0.0009343977,0.0005033769,0.00007777548,0.00024527695,0.5022621,0.00016973031,0.04169559,0.28064874,0.000579763],"about_ca_topic_score_codex":0.00042611247,"about_ca_topic_score_gemma":0.0036276174,"teacher_disagreement_score":0.7979153,"about_ca_system_score_codex":0.0004431116,"about_ca_system_score_gemma":0.0010650572,"threshold_uncertainty_score":0.9944707},"labels":[],"label_agreement":null},{"id":"W2891317412","doi":"10.23889/ijpds.v3i4.678","title":"The Cycle of Child Protection Services Involvement: A Cohort Study of Adolescent Mothers","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child Abuse and Trauma","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"","keywords":"Odds; Medicine; Odds ratio; Logistic regression; Cohort; Demography; Pediatrics; Child care; Population; Cohort study; Child protection; Family medicine; Nursing; Environmental health","score_opus":0.053636153357372075,"score_gpt":0.38242457849887396,"score_spread":0.32878842514150186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891317412","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99541163,0.000023394847,0.00091374625,0.00039523494,0.0021888504,0.0005594287,0.000053717566,0.000006889203,0.00044707855],"genre_scores_gemma":[0.9994543,0.000007963938,0.00006995337,0.00007436635,0.00032917407,0.000010184256,0.00001848915,0.0000050604926,0.000030506173],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99861676,0.00003528001,0.0003814553,0.00021165602,0.0006409176,0.000113919115],"domain_scores_gemma":[0.998615,0.000023426088,0.00044762908,0.0003825995,0.00049730414,0.000034040517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011703608,0.00005796218,0.00007544281,0.00014938044,0.00037086708,0.000081116006,0.0013092353,0.00001710692,0.000059551596],"category_scores_gemma":[0.000051022565,0.00004065998,0.000026724605,0.00020125424,0.0001496234,0.0005429083,0.00013404102,0.00007976042,0.000005312857],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000606857,0.001349809,0.93721706,0.000012848495,0.00035510855,0.0000012563977,0.004664556,0.0002172813,0.0005676779,0.0055175107,0.00048562762,0.049004417],"study_design_scores_gemma":[0.00079153257,0.00024142538,0.99139047,0.00006350648,0.000019376073,0.000018511733,0.0014493499,0.0031479981,0.00018847744,0.0004989308,0.002141123,0.000049288396],"about_ca_topic_score_codex":0.000808362,"about_ca_topic_score_gemma":0.0008371014,"teacher_disagreement_score":0.05417343,"about_ca_system_score_codex":0.000040886225,"about_ca_system_score_gemma":0.000022675044,"threshold_uncertainty_score":0.28524473},"labels":[],"label_agreement":null},{"id":"W2891327136","doi":"10.23889/ijpds.v3i4.1003","title":"Ontario case costing: A catalyst for transforming Ontario’s health system into a value-based model","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Activity-based costing; Benchmarking; Business; Health care; Operations management; Process management; Accounting; Marketing; Economics","score_opus":0.39335817448465704,"score_gpt":0.5505215869523673,"score_spread":0.15716341246771026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891327136","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2823836,0.000006772874,0.7076867,0.006554472,0.0019429566,0.001038405,0.00029805553,0.000030363517,0.000058659814],"genre_scores_gemma":[0.83956724,6.6103865e-7,0.15699482,0.0014266345,0.00057283405,0.000025067617,0.0012623663,0.000014211875,0.0001361938],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968046,0.000027848972,0.0013535109,0.0004900402,0.0010065776,0.00031742317],"domain_scores_gemma":[0.99634856,0.00035639413,0.00077529054,0.00042039182,0.0017917847,0.00030755694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050434778,0.00014247627,0.00023855355,0.00035022912,0.0008918221,0.00027287443,0.0006751895,0.000045301436,0.000033021297],"category_scores_gemma":[0.0026601786,0.0001297422,0.00010212464,0.00019041676,0.000127271,0.0021358926,0.00009552867,0.00022951503,0.000004691544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.018223641,0.00282395,0.27659363,0.0012567148,0.0013565054,0.00095143024,0.031266514,0.05738668,0.008253336,0.0502532,0.03557719,0.5160572],"study_design_scores_gemma":[0.004107891,0.00061087625,0.0022518726,0.00032602964,0.00013932156,0.003688886,0.00055484026,0.96894395,0.00014861354,0.0006532696,0.018393187,0.00018123937],"about_ca_topic_score_codex":0.32571572,"about_ca_topic_score_gemma":0.7556498,"teacher_disagreement_score":0.9115573,"about_ca_system_score_codex":0.0045704027,"about_ca_system_score_gemma":0.006208187,"threshold_uncertainty_score":0.9994257},"labels":[],"label_agreement":null},{"id":"W2891329851","doi":"10.23889/ijpds.v3i4.896","title":"International comparison in walkable environments and hospital burden in type 2 diabetes patients","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"","keywords":"Welsh; Neighbourhood (mathematics); Geography; Environmental health; Walkability; Health care; Type 2 diabetes; Medicine; Physical activity; Diabetes mellitus; Political science","score_opus":0.03860488224526202,"score_gpt":0.3741369762494719,"score_spread":0.33553209400420986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891329851","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949461,0.000024529474,0.000101344514,0.0008252526,0.0033113435,0.00015811028,0.00005743338,0.0000057101242,0.00057012896],"genre_scores_gemma":[0.9982982,0.000045891502,0.0008619215,0.000045837718,0.00046862237,0.0000025169893,0.00018305393,0.000003909216,0.00009004034],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99830157,0.000028546103,0.00035742103,0.0003034057,0.00078403065,0.0002250121],"domain_scores_gemma":[0.9993702,0.00004489618,0.00017174256,0.0001327448,0.00019865594,0.00008172827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012112618,0.00006792114,0.000091370035,0.00026482446,0.00026529364,0.00030312414,0.0013158082,0.00003783185,0.00010919037],"category_scores_gemma":[0.00059673475,0.00006649296,0.000014030612,0.00024924282,0.00037257187,0.0030583232,0.00017117555,0.000093895316,0.0000052715063],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021601949,0.00008572856,0.9866834,6.6847895e-7,0.0000041372436,5.9074875e-7,0.0009128751,0.000018336938,0.000046794034,0.00026613477,0.00017223907,0.011787436],"study_design_scores_gemma":[0.00046781084,0.000041031006,0.9688241,0.000026664859,0.0000022825614,1.07115866e-7,0.00021539512,0.0052469308,0.000023424798,0.0012668878,0.023798242,0.00008714281],"about_ca_topic_score_codex":0.0011564296,"about_ca_topic_score_gemma":0.002205567,"teacher_disagreement_score":0.023626002,"about_ca_system_score_codex":0.00025870808,"about_ca_system_score_gemma":0.00007727025,"threshold_uncertainty_score":0.2923033},"labels":[],"label_agreement":null},{"id":"W2891337205","doi":"10.23889/ijpds.v3i4.761","title":"Using Biomedical Text as Data and Representation Learning for Identifying Patients with an Osteoarthritis Phenotype in the Electronic Medical Record","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Institute for Clinical Evaluative Sciences; University of Toronto","funders":"","keywords":"Artificial intelligence; Machine learning; Computer science; Identification (biology); Supervised learning; Population; Support vector machine; Random forest; Representation (politics); Natural language processing; Medicine; Artificial neural network; Biology","score_opus":0.09758331678051675,"score_gpt":0.44003223897057725,"score_spread":0.3424489221900605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891337205","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9269395,0.0000573099,0.07187184,0.00045355552,0.00046608754,0.00014037082,0.000057712008,0.000004257498,0.000009390525],"genre_scores_gemma":[0.9872242,0.000034704914,0.010103452,0.0001627197,0.0005497125,0.0000037379425,0.0019079489,0.00000593105,0.000007596117],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9985334,0.00005806819,0.00022312072,0.00037463033,0.00062133773,0.00018939811],"domain_scores_gemma":[0.9991875,0.000060472415,0.00014214433,0.00029339554,0.00024445038,0.00007202516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001677184,0.00006291627,0.00006366583,0.000097120326,0.00031014008,0.00019261807,0.0013541018,0.000058299825,0.000009834139],"category_scores_gemma":[0.0029185335,0.000044082655,0.000009907376,0.00013956086,0.00030176682,0.00013567889,0.00032643514,0.000118250624,4.782805e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008290719,0.0001688028,0.22564712,0.000008936957,0.000046156605,0.000004939332,0.00033066527,0.000017145685,0.0047684936,0.00067271374,0.0006891573,0.7668168],"study_design_scores_gemma":[0.0112268245,0.00831286,0.4706706,0.0004681924,0.00010361489,0.00078972575,0.003101335,0.33254942,0.00075493293,0.0076547726,0.16350512,0.00086257566],"about_ca_topic_score_codex":0.00009706811,"about_ca_topic_score_gemma":0.0003863524,"teacher_disagreement_score":0.7659542,"about_ca_system_score_codex":0.000023305998,"about_ca_system_score_gemma":0.00019876288,"threshold_uncertainty_score":0.3493968},"labels":[],"label_agreement":null},{"id":"W2891356630","doi":"10.23889/ijpds.v3i4.868","title":"Harmonization of data from cohort studies– potential challenges and opportunities","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Comparability; Harmonization; Missing data; Imputation (statistics); Computer science; Data quality; Statistics; Data mining; Mathematics; Engineering","score_opus":0.47319052288278185,"score_gpt":0.5105984239167461,"score_spread":0.0374079010339643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891356630","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8176426,0.014124317,0.029357944,0.10117443,0.027792582,0.0010462038,0.0059715407,0.000095170995,0.0027952096],"genre_scores_gemma":[0.97022545,0.021431291,0.0056855185,0.00046378988,0.0015873805,0.00000139165,0.00046824565,0.000005010849,0.00013190821],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9982671,0.000060588765,0.00034218852,0.00028065225,0.00087141705,0.00017806202],"domain_scores_gemma":[0.99802536,0.0001661772,0.00028348624,0.00032785503,0.0010747493,0.00012235796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028886157,0.0000584496,0.000117039475,0.00013781036,0.0007179117,0.00018886157,0.0017752874,0.00003156385,0.000056775098],"category_scores_gemma":[0.0017079874,0.0000530819,0.00001244001,0.000071622744,0.00070296373,0.003848211,0.00057873776,0.00005230643,0.0000015813116],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020641873,0.00014417141,0.09591192,0.00006774256,0.0004772332,0.000016180771,0.01308163,0.000023191153,0.00024248648,0.35754967,0.018400325,0.513879],"study_design_scores_gemma":[0.0008075048,0.00008944368,0.72071636,0.00030231426,0.00011682222,0.000032089036,0.021575633,0.022987628,0.000049911712,0.033561666,0.19941692,0.00034372325],"about_ca_topic_score_codex":0.0018485879,"about_ca_topic_score_gemma":0.0021044866,"teacher_disagreement_score":0.62480444,"about_ca_system_score_codex":0.000076846976,"about_ca_system_score_gemma":0.0003174084,"threshold_uncertainty_score":0.5521669},"labels":[],"label_agreement":null},{"id":"W2891357407","doi":"10.23889/ijpds.v3i4.723","title":"In Sickness and In Health: Effects of Cardiovascular Health Shocks on Spouses’ Work and Earnings","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Earnings; Shock (circulatory); Workforce; Spouse; Stroke (engine); Medicine; Demography; Demographic economics; Economics; Internal medicine; Finance; Political science","score_opus":0.08254226779907171,"score_gpt":0.46873880679390106,"score_spread":0.38619653899482936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891357407","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9872195,0.0004957672,0.0007479165,0.009405406,0.0016379016,0.0004361686,0.000022823535,0.000006306625,0.000028176106],"genre_scores_gemma":[0.99808663,0.0004454874,0.00041376543,0.0007167024,0.00024328384,0.000009585849,0.000017091648,0.00000591458,0.0000615465],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983696,0.00015550124,0.00049606996,0.000253728,0.00047834794,0.00024675005],"domain_scores_gemma":[0.9989511,0.00029619725,0.00030893862,0.00016926853,0.0001917304,0.00008277371],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032955767,0.00007326115,0.00021588731,0.00037468833,0.0004743303,0.000021904701,0.00034211302,0.000027557364,0.0000063206276],"category_scores_gemma":[0.00089388894,0.00006199703,0.00001917669,0.00026802934,0.00014794778,0.00062307215,0.0002561074,0.00020273091,0.0000011652991],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012346369,0.000031262454,0.98294634,0.00009371467,0.000023034825,0.0000022980373,0.0020666844,0.00006229428,0.000008482471,0.0013294375,0.00093165756,0.0123813385],"study_design_scores_gemma":[0.00093661604,0.00013775776,0.9856921,0.0008170575,0.0000026641592,0.0000032596488,0.00017279011,0.00028288513,0.0000052027412,0.0005858867,0.011305916,0.00005786718],"about_ca_topic_score_codex":0.0017834482,"about_ca_topic_score_gemma":0.00062492094,"teacher_disagreement_score":0.012323471,"about_ca_system_score_codex":0.00018128075,"about_ca_system_score_gemma":0.00017019831,"threshold_uncertainty_score":0.3648213},"labels":[],"label_agreement":null},{"id":"W2891367361","doi":"10.23889/ijpds.v3i4.1007","title":"Understanding Patterns of Emergency Department (ED) Use over time in Ontario to plan new EDs for the future","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Emergency department; Population; Christian ministry; Medicine; Demography; Health care; Medical emergency; Portfolio; Emergency medicine; Gerontology; Business; Environmental health; Psychiatry; Political science; Sociology; Finance","score_opus":0.19236091432256083,"score_gpt":0.40480061274800166,"score_spread":0.21243969842544083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891367361","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87079483,0.00019499884,0.10221483,0.010480307,0.014081366,0.0010908861,0.0010106813,0.000013064956,0.00011900712],"genre_scores_gemma":[0.993767,0.00019611302,0.0029242134,0.000417777,0.0015746845,0.0000073732763,0.00030011623,0.000007792981,0.0008048869],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988283,0.0000061306614,0.00033058014,0.00018714141,0.00049729925,0.00015058139],"domain_scores_gemma":[0.9992104,0.000055351986,0.00014002224,0.00019919274,0.00031764197,0.00007739538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004671919,0.00007275253,0.000099674624,0.00016588278,0.00020347274,0.00004290374,0.00051858014,0.000019809631,0.00028712768],"category_scores_gemma":[0.00027503062,0.0000495552,0.000047952824,0.00013449148,0.000030657062,0.00069326826,0.00014378867,0.00007541617,0.0000022174058],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046169563,0.00005853235,0.8625292,0.0000070049578,0.00011838648,0.0000026419607,0.0009021299,0.00009586077,0.00064629974,0.0032157972,0.128378,0.003584453],"study_design_scores_gemma":[0.00088527595,0.0002769653,0.86103046,0.00013352965,0.000053707336,0.000020125617,0.00027086836,0.002732494,0.00010663919,0.0014560963,0.13292277,0.00011106646],"about_ca_topic_score_codex":0.002577474,"about_ca_topic_score_gemma":0.054018237,"teacher_disagreement_score":0.12297218,"about_ca_system_score_codex":0.0003083006,"about_ca_system_score_gemma":0.00018275084,"threshold_uncertainty_score":0.9632435},"labels":[],"label_agreement":null},{"id":"W2891376554","doi":"10.23889/ijpds.v3i4.851","title":"Through the legal maze: An Act Respecting Research","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Government of New Brunswick; University of New Brunswick","funders":"","keywords":"Legislature; Government (linguistics); Legislation; Public administration; Political science; Public relations; Sociology; Law","score_opus":0.8484221759474988,"score_gpt":0.7452109123072294,"score_spread":0.10321126364026945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891376554","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8337819,0.000070240865,0.014314485,0.12955287,0.008247477,0.0009184308,0.00016051196,0.00006690362,0.012887168],"genre_scores_gemma":[0.97909766,0.000059487167,0.013824751,0.0009670309,0.0043584057,0.0000049259766,0.00007309823,0.000012942718,0.0016016765],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99378186,0.00014896241,0.0004994243,0.00050827157,0.00464419,0.00041729928],"domain_scores_gemma":[0.9885321,0.0032457921,0.00019485655,0.001091319,0.006741318,0.0001945809],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.02783914,0.00007477368,0.00010236813,0.00028382326,0.0013727293,0.00097339257,0.0038254613,0.00008495103,0.00018804747],"category_scores_gemma":[0.06280127,0.00004849438,0.00004562293,0.00067099836,0.0015360343,0.0031455639,0.0009976547,0.0016246012,0.00005220669],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022622752,0.0005297166,0.05264341,0.000030751216,0.0001422031,0.00010522552,0.0024767306,0.000073228795,0.014174441,0.8305899,0.024392858,0.07257928],"study_design_scores_gemma":[0.002061556,0.0018474164,0.17829473,0.0005125486,0.000032226188,0.0015561095,0.0017238683,0.048357397,0.0028238115,0.36279863,0.39970994,0.00028175904],"about_ca_topic_score_codex":0.0006432107,"about_ca_topic_score_gemma":0.00084305136,"teacher_disagreement_score":0.46779126,"about_ca_system_score_codex":0.0003201028,"about_ca_system_score_gemma":0.0013743653,"threshold_uncertainty_score":0.99992734},"labels":[],"label_agreement":null},{"id":"W2891377679","doi":"10.23889/ijpds.v3i4.911","title":"First Nations Data Governance, Privacy, and the Importance of the OCAP® principles","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Acronym; Internet privacy; Information privacy; Privacy by Design; Corporate governance; Realm; Privacy policy; Privacy law; Data governance; Political science; Public relations; Computer science; Business; Law; Data quality","score_opus":0.5234185834369959,"score_gpt":0.5876122302660017,"score_spread":0.06419364682900586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891377679","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7046955,0.0005781519,0.013262725,0.262429,0.0077206674,0.0020507097,0.0030844347,0.000032721073,0.0061460542],"genre_scores_gemma":[0.99071133,0.000618732,0.006839987,0.0005121428,0.00061118347,0.0000038567728,0.000080238344,0.0000060471425,0.0006164851],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9969468,0.00003391854,0.00053484156,0.00033848608,0.0019988257,0.00014711317],"domain_scores_gemma":[0.991522,0.0037016352,0.0006496131,0.001943784,0.0020795688,0.000103411294],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.007974903,0.000062515996,0.000112203816,0.0000782866,0.00080080016,0.00016836908,0.0048247194,0.000044891112,0.000043969165],"category_scores_gemma":[0.08598005,0.000033154232,0.000034533085,0.0003772039,0.0020962737,0.001099271,0.002902872,0.00040544075,0.0000024529922],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028836,0.0000685294,0.3821766,0.000029874942,0.000055954173,0.000001380198,0.00015925642,0.000027955564,0.0000875453,0.61350316,0.0020582469,0.0015431549],"study_design_scores_gemma":[0.001662859,0.000060019636,0.82928,0.00037737974,0.00003606888,0.00014729523,0.000047733683,0.07526285,0.00009772743,0.03686966,0.056089614,0.000068765345],"about_ca_topic_score_codex":0.00010667244,"about_ca_topic_score_gemma":0.003170823,"teacher_disagreement_score":0.5766335,"about_ca_system_score_codex":0.00008351549,"about_ca_system_score_gemma":0.00064547535,"threshold_uncertainty_score":0.92171913},"labels":[],"label_agreement":null},{"id":"W2891379132","doi":"10.23889/ijpds.v3i4.635","title":"No Strings Attached: The Impact of an Unconditional Prenatal Income Supplement on First Nations Birth and Early Childhood Outcomes","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Breastfeeding Practices and Influences","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; First Nations Health and Social Secretariat of Manitoba; Manitoba Health","funders":"","keywords":"Medicine; Relative risk; Breastfeeding; Demography; Pregnancy; Birth certificate; Population; Low birth weight; Birth weight; Gestational age; Prenatal care; Obstetrics; Pediatrics; Environmental health; Confidence interval","score_opus":0.042106661710494826,"score_gpt":0.4116014203095986,"score_spread":0.3694947585991038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891379132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941067,0.000006441998,0.00016891948,0.0034302506,0.0006405341,0.0002042473,0.0012490335,0.00000891884,0.00018493236],"genre_scores_gemma":[0.996703,0.000009286504,0.002329994,0.00007688016,0.00050789973,0.000004384602,0.00031468752,0.0000055844757,0.00004823763],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984167,0.000014852898,0.0003345999,0.00022598526,0.0008672127,0.00014065548],"domain_scores_gemma":[0.99828523,0.00019877427,0.00036634775,0.00024384205,0.00078874046,0.0001170654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092158373,0.0000918926,0.00010813765,0.00031683527,0.00067542045,0.0002549737,0.0007130174,0.00002303567,0.00017046549],"category_scores_gemma":[0.0011892444,0.00005477724,0.000051159583,0.00019697093,0.00027599317,0.0027362728,0.00016414541,0.00012694347,0.0000050468097],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022020008,0.00022833282,0.98857135,0.0000074709887,0.00014876308,0.0000017062433,0.00037695694,0.00018906056,0.00007698345,0.0059321774,0.00033684302,0.0039101676],"study_design_scores_gemma":[0.00080371,0.0007615354,0.9933505,0.00008843571,0.000019813337,0.00018960515,0.00003351395,0.003147818,0.000067213834,0.0004337873,0.0010433414,0.000060739156],"about_ca_topic_score_codex":0.00094164046,"about_ca_topic_score_gemma":0.00019218706,"teacher_disagreement_score":0.00549839,"about_ca_system_score_codex":0.00010185114,"about_ca_system_score_gemma":0.00017532069,"threshold_uncertainty_score":0.51948565},"labels":[],"label_agreement":null},{"id":"W2891383430","doi":"10.23889/ijpds.v3i4.874","title":"Linking surveillance and administrative data to better understand dementia’s impact in Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Aging, Elder Care, and Social Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Public Health Agency of Canada; Canadian Institute for Health Information","funders":"","keywords":"Dementia; Medicine; Public health; Health care; Agency (philosophy); Gerontology; Nursing homes; Family medicine; Nursing; Disease","score_opus":0.24596163527707082,"score_gpt":0.5248256199901169,"score_spread":0.2788639847130461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891383430","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98697877,0.000044693898,0.006132274,0.0026706674,0.0025255608,0.0002602479,0.0011115227,0.0000066423845,0.00026963075],"genre_scores_gemma":[0.9954107,0.000017407454,0.0017247016,0.0015837967,0.0007834032,0.0000022530598,0.0004397196,0.000006043164,0.00003198703],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983268,0.000078464866,0.0003792362,0.0003304923,0.00060095853,0.00028408095],"domain_scores_gemma":[0.9986401,0.0002046519,0.00022745227,0.00032849246,0.000452058,0.00014723616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001708951,0.000079321726,0.00011368648,0.00014049673,0.00074394484,0.00012830402,0.0013751967,0.000027630522,0.00006685949],"category_scores_gemma":[0.0007298925,0.00006871571,0.000008922527,0.00018955575,0.00008555222,0.0013833515,0.0006087557,0.00018631219,0.0000029629348],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003732065,0.0000055588066,0.9892082,0.000004098021,0.000021635804,0.000004227217,0.0021594607,0.000009042481,0.00004293687,0.00026095164,0.0048668915,0.0033796367],"study_design_scores_gemma":[0.00043107264,0.00004384839,0.97659236,0.00014068752,0.000006395552,0.000006685929,0.006017124,0.006941165,0.000005305687,0.0016725851,0.008009377,0.00013337468],"about_ca_topic_score_codex":0.38449332,"about_ca_topic_score_gemma":0.9452192,"teacher_disagreement_score":0.5607259,"about_ca_system_score_codex":0.0007387003,"about_ca_system_score_gemma":0.0020336013,"threshold_uncertainty_score":0.61960536},"labels":[],"label_agreement":null},{"id":"W2891383683","doi":"10.23889/ijpds.v3i4.639","title":"Population survival impact of new targeted and immune based therapies for metastatic or unresectable melanoma","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cancer Immunotherapy and Biomarkers","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Northeast Cancer Centre; Queen's University","funders":"","keywords":"Medicine; Population; Hazard ratio; Cancer registry; Internal medicine; Cohort; Cancer; Oncology; Radiation therapy; Melanoma; Systemic therapy; Relative survival; Retrospective cohort study; Christian ministry; Confidence interval; Cancer research","score_opus":0.10322139556213399,"score_gpt":0.4381719238084799,"score_spread":0.3349505282463459,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891383683","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9574254,0.00032643473,0.03873017,0.000921957,0.0014615777,0.0005308652,0.00056787464,0.000014533679,0.000021142925],"genre_scores_gemma":[0.9759522,0.00003188191,0.022783583,0.00006919795,0.00033440726,0.0000033765034,0.0006283389,0.000011010348,0.0001860084],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986167,0.000022303795,0.0004366321,0.00022421472,0.0005280969,0.00017206294],"domain_scores_gemma":[0.99853516,0.00014199702,0.00034967193,0.00023783342,0.0006413865,0.000093947114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012442133,0.00010215203,0.0001997031,0.0003173559,0.0002122574,0.0001302688,0.00043658714,0.000025791354,0.00023923004],"category_scores_gemma":[0.0006911619,0.000068940164,0.00009103364,0.00027744498,0.0001487631,0.0010011542,0.00005040915,0.00005118832,4.4956772e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.05710156,0.0004784334,0.38372993,0.00012456115,0.001860383,0.000008051163,0.00095310423,0.00031738722,0.23743896,0.0018032895,0.005756316,0.31042802],"study_design_scores_gemma":[0.006740289,0.0018035267,0.9129914,0.0001631866,0.000098431185,0.00012734778,0.00013427396,0.070392154,0.0037811496,0.0014768271,0.0021250176,0.00016641522],"about_ca_topic_score_codex":0.0019927185,"about_ca_topic_score_gemma":0.00023545459,"teacher_disagreement_score":0.52926147,"about_ca_system_score_codex":0.00013632845,"about_ca_system_score_gemma":0.0004882401,"threshold_uncertainty_score":0.30124077},"labels":[],"label_agreement":null},{"id":"W2891387775","doi":"10.23889/ijpds.v3i4.826","title":"Using linked administrative, clinical and primary data to explore the impact of and factors associated with non-adherence to in-hospital medication changes in 30-days post hospital discharge","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University Health Centre; Université de Montréal; University of British Columbia; McGill University","funders":"","keywords":"Medicine; Medical prescription; Emergency medicine; Emergency department; Hospital discharge; Adverse effect; Community hospital; Health care; Intensive care medicine; Internal medicine","score_opus":0.5479923548710948,"score_gpt":0.571223637326622,"score_spread":0.02323128245552719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891387775","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949203,0.000011421597,0.00050552405,0.0032831081,0.00037841278,0.0005193567,0.00036848115,0.0000028788636,0.000010493493],"genre_scores_gemma":[0.99823254,0.000026568476,0.0010540365,0.00018745581,0.00013742219,0.000003025798,0.0003505318,0.0000054056704,0.0000030133074],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99856067,0.000043232954,0.00038878006,0.00031385617,0.0005404424,0.00015303398],"domain_scores_gemma":[0.99857914,0.00032323634,0.00030402423,0.0002581723,0.00034629423,0.00018914089],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015061719,0.00009115187,0.0001708578,0.00018287625,0.00010033322,0.000093260685,0.00064841163,0.000032631455,0.000015988895],"category_scores_gemma":[0.0037193974,0.000053838543,0.000014624432,0.00026595735,0.00025875782,0.0013891748,0.00040407252,0.0001798655,5.0475273e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021191293,0.00017373991,0.99564934,0.000003936541,0.00002987473,0.000002132605,0.0009440432,0.0000060002926,0.0006456008,0.000017837116,0.000058419104,0.002257176],"study_design_scores_gemma":[0.00085700746,0.0016746754,0.97004586,0.00021027273,0.000021109661,0.0000071212276,0.00041450118,0.026593214,0.000031502874,0.000030943836,0.000042218162,0.00007153905],"about_ca_topic_score_codex":0.00024242062,"about_ca_topic_score_gemma":0.00026477786,"teacher_disagreement_score":0.026587214,"about_ca_system_score_codex":0.00009153727,"about_ca_system_score_gemma":0.00021394702,"threshold_uncertainty_score":0.4452735},"labels":[],"label_agreement":null},{"id":"W2891397251","doi":"10.23889/ijpds.v3i4.658","title":"Depressive episodes, weight change, and incident diabetes in a Canadian community sample","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"CIDI; Depression (economics); Medicine; Population; Demography; Community health; Gerontology; Incidence (geometry); Weight change; Diabetes mellitus; Psychiatry; Weight loss; Obesity; Environmental health; Public health; National Comorbidity Survey","score_opus":0.08705414557077543,"score_gpt":0.36663048330440107,"score_spread":0.27957633773362567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891397251","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964971,0.00024926127,0.0004854538,0.00097376906,0.0009922177,0.0003270066,0.0003590119,0.000009491467,0.00010669881],"genre_scores_gemma":[0.995334,0.00007616406,0.0027606618,0.0005865201,0.0007928851,0.000017793613,0.00040895256,0.000008562958,0.000014419186],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985867,0.000060285354,0.0002552779,0.00021841312,0.00056876417,0.00031054454],"domain_scores_gemma":[0.9985652,0.00009563741,0.0001194914,0.00040825715,0.0004936956,0.00031771202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002127706,0.000088456916,0.00016263154,0.00053892075,0.00045396914,0.00019824578,0.0007483228,0.000039549854,0.000033356824],"category_scores_gemma":[0.0021318696,0.000078661426,0.000040637413,0.00023087882,0.00024269082,0.0013641131,0.00024505839,0.00021833055,0.0000037576442],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024162811,0.000036405792,0.85964495,0.000008118923,0.00004668068,0.0000072388516,0.00025924173,0.0000035447772,0.00007785782,0.00030386087,0.00027907456,0.13930887],"study_design_scores_gemma":[0.000720745,0.000080897815,0.9707809,0.00012692182,0.000024717048,0.00006243417,0.00005370196,0.008577436,0.00021907587,0.0017945718,0.01746649,0.00009212268],"about_ca_topic_score_codex":0.6726615,"about_ca_topic_score_gemma":0.72594327,"teacher_disagreement_score":0.13921675,"about_ca_system_score_codex":0.0003003641,"about_ca_system_score_gemma":0.00025198032,"threshold_uncertainty_score":0.34916094},"labels":[],"label_agreement":null},{"id":"W2891423315","doi":"10.23889/ijpds.v3i4.755","title":"Intergenerational teen pregnancy: a population based cohort study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Reproductive Health and Contraception","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Women's College Hospital; University of Manitoba; Mount Sinai Hospital; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Pregnancy; Daughter; Abortion; Teen pregnancy; Demography; Odds ratio; Population; Medicine; Odds; Obstetrics; Fertility; National Survey of Family Growth; Logistic regression; Psychology; Gynecology; Family planning; Research methodology; Sociology; Biology; Genetics","score_opus":0.08096589001602789,"score_gpt":0.4382558113319862,"score_spread":0.3572899213159583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891423315","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9593417,0.000028310738,0.03151783,0.00282304,0.0045422693,0.0014092865,0.00010022595,0.00004449274,0.00019284018],"genre_scores_gemma":[0.9883313,0.0000061800038,0.0069652563,0.0003729214,0.0029128282,0.000042737367,0.0011033781,0.000012725959,0.00025268362],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972184,0.000048873782,0.00056325656,0.0005940146,0.0013419648,0.00023350673],"domain_scores_gemma":[0.9969888,0.000038574228,0.0003263989,0.00053885014,0.0019306152,0.00017681312],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017575851,0.000120678895,0.00016287992,0.00043079007,0.0005465738,0.00022707813,0.0006579586,0.000038683986,0.00019438488],"category_scores_gemma":[0.0014284666,0.000102857986,0.00004978696,0.0003166437,0.00009945544,0.0018249479,0.00010661009,0.00014186287,0.000020946272],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002942451,0.0002510637,0.98008806,0.000005165883,0.00003659572,0.000003561357,0.00005140098,0.00007069321,0.0008785553,0.00048041693,0.0007675402,0.017072733],"study_design_scores_gemma":[0.0011715589,0.00040718156,0.9514591,0.000080804864,0.00004183395,0.0000786446,0.000032929078,0.044109207,0.00012886431,0.00039562662,0.0019943828,0.00009986422],"about_ca_topic_score_codex":0.0002738761,"about_ca_topic_score_gemma":0.00017907089,"teacher_disagreement_score":0.044038516,"about_ca_system_score_codex":0.0003654862,"about_ca_system_score_gemma":0.00039962216,"threshold_uncertainty_score":0.42038587},"labels":[],"label_agreement":null},{"id":"W2891439728","doi":"10.23889/ijpds.v3i4.652","title":"Trajectory of service use among young Albertans with complex needs","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Government (linguistics); Service (business); Mental health; Economic Justice; Service provider; Population; Trajectory; Psychological intervention; Psychology; Medicine; Business; Environmental health; Nursing; Psychiatry; Political science; Marketing","score_opus":0.35123236987446005,"score_gpt":0.5094037475565065,"score_spread":0.15817137768204648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891439728","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.985391,0.000006162894,0.006519618,0.002045154,0.0036440452,0.00049928325,0.0008508702,0.000032034222,0.0010117935],"genre_scores_gemma":[0.9882929,0.000008821348,0.008845357,0.0011665059,0.0007659085,0.000010671385,0.00057709,0.000012951833,0.00031983547],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99756455,0.000098279575,0.00074502925,0.00027252734,0.0009624175,0.00035722047],"domain_scores_gemma":[0.9953794,0.00032390337,0.0007314925,0.00046168544,0.0028689862,0.00023457246],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0015328951,0.00011247769,0.00016318867,0.00055393996,0.00178975,0.00010261279,0.0015862714,0.00007721547,0.0004398477],"category_scores_gemma":[0.0010178802,0.000095034935,0.000031166866,0.0007054517,0.00039385367,0.003693153,0.00029234614,0.0002960963,0.00002523286],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024682266,0.00004972222,0.97633517,0.000035254332,0.000032296255,0.0000010905113,0.0033175012,0.00028648096,0.00018632518,0.01610225,0.003186098,0.00022097348],"study_design_scores_gemma":[0.00087896665,0.00010876798,0.9570747,0.0001709126,0.000021476151,0.000021349118,0.001132522,0.026322836,0.00001016172,0.0006607036,0.013473483,0.00012410012],"about_ca_topic_score_codex":0.0079259565,"about_ca_topic_score_gemma":0.019886054,"teacher_disagreement_score":0.026036354,"about_ca_system_score_codex":0.00023583918,"about_ca_system_score_gemma":0.0005961572,"threshold_uncertainty_score":0.9995098},"labels":[],"label_agreement":null},{"id":"W2891442307","doi":"10.23889/ijpds.v3i4.839","title":"Development of an automated system for clinical study recruitment","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Calgary Laboratory Services; University of Alberta; Alberta Health Services","funders":"","keywords":"Medicine; CLs upper limits; Medical emergency; Emergency medicine; Analytics; Creatinine; Database; Internal medicine; Computer science","score_opus":0.34316856558312436,"score_gpt":0.5074725869746233,"score_spread":0.1643040213914989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891442307","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9740305,0.000004686108,0.016862322,0.0003870202,0.0071181846,0.0010393376,0.000054183354,0.00012223756,0.00038154985],"genre_scores_gemma":[0.9651362,0.0000011428192,0.03320089,0.00016861469,0.0012230437,0.000024953722,0.00021956649,0.000007752045,0.000017868246],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99803555,0.000014843241,0.00077088474,0.000307482,0.00074499456,0.00012623733],"domain_scores_gemma":[0.997127,0.000071965194,0.0007168589,0.0002426028,0.001815686,0.000025871419],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004939947,0.00007739966,0.00011869926,0.00034952036,0.00054457097,0.000542531,0.001318284,0.000024918354,0.000033045548],"category_scores_gemma":[0.0006546504,0.00006478963,0.000029765673,0.00028500857,0.00007424809,0.0055019557,0.0001927672,0.00005336555,0.0000125616925],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020083971,0.0047714626,0.17701335,0.00014814944,0.0005695046,0.000009393439,0.0009422859,0.0001630565,0.0021136005,0.07120754,0.005946835,0.7351064],"study_design_scores_gemma":[0.00452204,0.00020997552,0.30794638,0.00011482713,0.00013038247,0.00002414931,0.002520091,0.40735066,0.0003233868,0.00048435706,0.27607462,0.00029910792],"about_ca_topic_score_codex":0.000054721466,"about_ca_topic_score_gemma":0.00020826753,"teacher_disagreement_score":0.7348073,"about_ca_system_score_codex":0.0000492773,"about_ca_system_score_gemma":0.0001409882,"threshold_uncertainty_score":0.5231639},"labels":[],"label_agreement":null},{"id":"W2891444423","doi":"10.23889/ijpds.v3i4.752","title":"Approaches to big data analysis of interface pressure measurements from continuous pressure imaging technology","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; University of Calgary","funders":"","keywords":"Position (finance); Data set; Frame (networking); Set (abstract data type); Sampling (signal processing); Similarity (geometry); Computer science; Correlation coefficient; Representation (politics); Correlation; Data mining; Pearson product-moment correlation coefficient; Statistics; Mathematics; Medicine; Artificial intelligence; Computer vision","score_opus":0.4441416042611032,"score_gpt":0.4510575532069361,"score_spread":0.006915948945832862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891444423","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81438684,0.00073491916,0.165211,0.010019409,0.0058576674,0.00066425937,0.002910012,0.00010255194,0.00011330953],"genre_scores_gemma":[0.98001796,0.0000073771503,0.01861518,0.00008258438,0.0005198914,0.0000045517168,0.0006867075,0.0000079113315,0.000057837104],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978531,0.000026880934,0.00050941063,0.00056416297,0.00082709274,0.0002193313],"domain_scores_gemma":[0.9973332,0.000044675784,0.0003650271,0.0012239836,0.0009185097,0.00011456772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013921616,0.000104474544,0.00026011368,0.0013114507,0.0002004596,0.00007018781,0.0027009256,0.000075033226,0.00002446931],"category_scores_gemma":[0.0020193828,0.000092223876,0.000034559704,0.0010843904,0.00024920204,0.00081234064,0.0010016357,0.00019887794,0.0000033704182],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019208311,0.000082876766,0.8751815,0.000009940878,0.0011401417,0.0000021313856,0.00016471371,0.00020757932,0.0049816887,0.00019100374,0.00069922756,0.11714712],"study_design_scores_gemma":[0.0018903301,0.00046475543,0.6284657,0.0006860455,0.0037922866,0.00009786469,0.0007026033,0.27039638,0.018798772,0.001217005,0.07305873,0.0004295091],"about_ca_topic_score_codex":0.00041242427,"about_ca_topic_score_gemma":0.00015807526,"teacher_disagreement_score":0.2701888,"about_ca_system_score_codex":0.000056655175,"about_ca_system_score_gemma":0.00015611653,"threshold_uncertainty_score":0.50190365},"labels":[],"label_agreement":null},{"id":"W2891451818","doi":"10.23889/ijpds.v3i4.824","title":"Lessons learned: Linking patient-reported outcomes data with administrative databases","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Cancer Care Ontario; Institute for Clinical Evaluative Sciences; Sunnybrook Health Science Centre; Manitoba Health; Health Sciences Centre; Sunnybrook Hospital","funders":"","keywords":"Medicine; Medical record; Data collection; Cancer; Cohort; Perspective (graphical); Disease; Missing data; Conversation; Cancer registry; Family medicine; Database; Psychology; Internal medicine; Computer science","score_opus":0.5260813958789775,"score_gpt":0.5476634899560613,"score_spread":0.02158209407708378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891451818","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89911205,0.000088450106,0.074747115,0.017382827,0.0035617193,0.0006123765,0.0031178226,0.000086045104,0.0012916249],"genre_scores_gemma":[0.9567733,0.000021400368,0.0386478,0.00079909945,0.00057569105,0.0000030459998,0.0030730444,0.000009823308,0.00009678555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971799,0.000018257575,0.00045024639,0.00058541505,0.0015106332,0.00025549353],"domain_scores_gemma":[0.99693865,0.00009138299,0.0004642964,0.0010414213,0.0012781637,0.00018606753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010864198,0.00012556366,0.00016825933,0.00021741363,0.0005041229,0.00032037587,0.0017129007,0.000024206242,0.000071314826],"category_scores_gemma":[0.0020369673,0.00009053421,0.000027221298,0.00031075007,0.00032319527,0.0040345644,0.00067630335,0.00018070216,0.000008217015],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011624814,0.00015925623,0.85587513,0.000010341442,0.00028469556,0.0002033742,0.00028436419,0.000063767664,0.0010888206,0.004629096,0.0053169676,0.13092172],"study_design_scores_gemma":[0.0034600454,0.0014135817,0.8059169,0.0011683924,0.00033170378,0.004130411,0.0015177344,0.039698493,0.0013143956,0.0013847421,0.13907869,0.0005848767],"about_ca_topic_score_codex":0.0003711802,"about_ca_topic_score_gemma":0.00055203633,"teacher_disagreement_score":0.13376173,"about_ca_system_score_codex":0.00013238618,"about_ca_system_score_gemma":0.0007217487,"threshold_uncertainty_score":0.38773566},"labels":[],"label_agreement":null},{"id":"W2891465197","doi":"10.23889/ijpds.v3i4.615","title":"Statistical Population Register: using administrative in the Canadian Census","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Census and Population Estimation","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Census; Population; Scope (computer science); Register (sociolinguistics); Geography; Data quality; Computer science; Statistics; Operations management; Engineering; Medicine; Environmental health","score_opus":0.40957507728501474,"score_gpt":0.5289055900918229,"score_spread":0.11933051280680818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891465197","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9053433,0.000013599777,0.07889252,0.0052879057,0.0055786334,0.0010045223,0.002164498,0.000038980037,0.0016760167],"genre_scores_gemma":[0.9499713,0.0000014246128,0.048162546,0.0002308713,0.00068628683,0.0000039670094,0.00090756174,0.0000099364215,0.000026083411],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9977105,0.00009207023,0.00059312064,0.00030866373,0.001003109,0.0002925067],"domain_scores_gemma":[0.9981035,0.00028279854,0.00037140894,0.0004013069,0.00070698204,0.00013398437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027454179,0.00011722687,0.000118881515,0.0004343765,0.00091233983,0.0005708404,0.0012701426,0.00005535132,0.0000555806],"category_scores_gemma":[0.0028790184,0.00009164895,0.000029118835,0.00039499672,0.00019484409,0.0015222145,0.00007660405,0.0001697302,0.000004476496],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000121288474,0.00010382959,0.18571351,0.0000119895885,0.0000234647,0.000024960556,0.0010096916,0.0003552705,0.00007293417,0.793845,0.004555651,0.014162389],"study_design_scores_gemma":[0.00051313493,0.00007011872,0.6356979,0.000069494134,0.000024614234,0.00034339368,0.0001621748,0.2129983,0.0000099871495,0.14238884,0.007517381,0.00020469133],"about_ca_topic_score_codex":0.034377135,"about_ca_topic_score_gemma":0.21203172,"teacher_disagreement_score":0.6514562,"about_ca_system_score_codex":0.00059316773,"about_ca_system_score_gemma":0.00034439546,"threshold_uncertainty_score":0.97205305},"labels":[],"label_agreement":null},{"id":"W2891466849","doi":"10.23889/ijpds.v3i4.978","title":"Quality assessment of linked Canadian clinical administrative hospital and vital statistics death data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Data quality; Linkage (software); Quality (philosophy); Record linkage; Health care; Medicine; Cohort; Set (abstract data type); Medical record; Quality Score; Data set; Summary statistics; Minimum Data Set; Computer science; Medical emergency; Database; Data mining; Statistics; Operations management; Engineering; Environmental health; Nursing; Internal medicine","score_opus":0.7700401790556543,"score_gpt":0.7013584868202501,"score_spread":0.0686816922354041,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891466849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5988028,0.00002142887,0.3424496,0.010273063,0.01846254,0.0012032867,0.025697751,0.000031419215,0.0030580636],"genre_scores_gemma":[0.94176495,0.000044971315,0.053951826,0.0006396075,0.0010142499,0.000003602082,0.0025175575,0.000004299133,0.000058921738],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971445,0.00017279114,0.0012714826,0.00028550017,0.0008472171,0.00027851015],"domain_scores_gemma":[0.9958668,0.00071964687,0.00088331796,0.00048954436,0.0015725363,0.0004681535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0094888285,0.00007422086,0.00016841463,0.0001861351,0.0010431194,0.000074057294,0.0014462466,0.0000826395,0.00012779032],"category_scores_gemma":[0.008002734,0.00006251494,0.000013458063,0.000114853974,0.0003243402,0.0016705323,0.0004395129,0.00039564748,0.000007842603],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056097295,0.000053201642,0.8955794,0.000041698615,0.000027933494,0.0000018030823,0.0005273346,0.0000016137728,0.000007558751,0.062750496,0.013553531,0.027399348],"study_design_scores_gemma":[0.0005823014,0.00022145035,0.9172467,0.00009458567,0.000009393712,0.0000049604146,0.000378616,0.06065474,5.1303647e-7,0.002318717,0.018410414,0.00007759045],"about_ca_topic_score_codex":0.009965387,"about_ca_topic_score_gemma":0.018857561,"teacher_disagreement_score":0.34296215,"about_ca_system_score_codex":0.00022432886,"about_ca_system_score_gemma":0.0036776306,"threshold_uncertainty_score":0.9990457},"labels":[],"label_agreement":null},{"id":"W2891477567","doi":"10.23889/ijpds.v3i4.866","title":"Population Analysis of the Settlement Movement in Western Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; University of Guelph","funders":"","keywords":"Settlement (finance); Population; Genealogy; Standardization; Geography; Political science; Economy; Sociology; History; Law; Economics; Demography","score_opus":0.03803221749166261,"score_gpt":0.35927908873991127,"score_spread":0.3212468712482487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891477567","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9860841,0.000020733396,0.0006220421,0.0056415806,0.005691604,0.00022663409,0.0010249027,0.0000044889757,0.00068389985],"genre_scores_gemma":[0.99857384,0.00001127173,0.00015179283,0.00036511762,0.00023621872,0.0000016603765,0.00010966803,0.0000019182776,0.0005485189],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981831,0.00004530323,0.00031091558,0.0001563648,0.0011604953,0.0001438267],"domain_scores_gemma":[0.9990336,0.000032740194,0.00026899416,0.0002199953,0.00037860076,0.00006612039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001469221,0.00003628456,0.00007883094,0.0007210784,0.0007627842,0.0002889703,0.0014059965,0.000016119868,0.00014880895],"category_scores_gemma":[0.00043414976,0.000035301553,0.000036989302,0.0009790024,0.00026757203,0.0008408362,0.00012518054,0.000052045158,6.7369535e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014018869,0.000026525047,0.97207487,0.0000015163396,0.00007492738,9.795962e-7,0.0012946354,0.0012181788,0.00005817277,0.01376175,0.0039812326,0.0074932105],"study_design_scores_gemma":[0.00009669136,0.0000049353216,0.89821315,0.000012443094,0.00003177145,3.1963035e-7,0.00020654479,0.002647729,0.000005194138,0.00050799013,0.0982292,0.00004402234],"about_ca_topic_score_codex":0.98327124,"about_ca_topic_score_gemma":0.9997636,"teacher_disagreement_score":0.09424797,"about_ca_system_score_codex":0.0020430726,"about_ca_system_score_gemma":0.0013238272,"threshold_uncertainty_score":0.58667964},"labels":[],"label_agreement":null},{"id":"W2891486657","doi":"10.23889/ijpds.v3i4.768","title":"Adherence to Breast Cancer Follow-up Care Guidelines for Vulnerable Populations in four Canadian provinces: a CanIMPACT study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Nova Scotia Health Authority; University of Toronto; Dalhousie University; CARE Canada; Queen's University; CancerCare Manitoba; BC Cancer Agency","funders":"","keywords":"Medicine; Breast cancer; Cancer; Guideline; Population; Cancer registry; Cohort; Family medicine; Health care; Demography; Retrospective cohort study; Pediatrics; Environmental health; Internal medicine","score_opus":0.4440959237409349,"score_gpt":0.5400761154351349,"score_spread":0.09598019169420002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891486657","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9774741,0.00009307929,0.003630028,0.0067022922,0.0056877574,0.0020064937,0.004188521,0.000024798454,0.00019295499],"genre_scores_gemma":[0.9873395,0.0000066741904,0.009653001,0.0011190682,0.001294782,0.000093567105,0.0002491449,0.000013626645,0.00023066663],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99752045,0.00002380305,0.0005855532,0.0004928232,0.00093688135,0.00044050743],"domain_scores_gemma":[0.9942642,0.00003815373,0.00019681951,0.0003643264,0.004685196,0.00045129383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013768609,0.0001442395,0.00019720614,0.00063815346,0.0006783814,0.0003296702,0.0011695267,0.000039909035,0.00009927869],"category_scores_gemma":[0.0030172928,0.00012440151,0.00005335122,0.00062474125,0.00006134534,0.0016523406,0.00012770362,0.00014416547,0.0000043191117],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056079077,0.000036889927,0.9361692,0.000011783212,0.00003506741,0.000016335704,0.0010448677,0.00084203907,0.00027553778,0.0002744979,0.014959576,0.045773435],"study_design_scores_gemma":[0.0028683194,0.0011663123,0.95603305,0.000646018,0.00007480748,0.0002982657,0.0048707165,0.022418424,0.00003514508,0.00045960562,0.010816483,0.00031286126],"about_ca_topic_score_codex":0.40589386,"about_ca_topic_score_gemma":0.8646484,"teacher_disagreement_score":0.4587545,"about_ca_system_score_codex":0.0016423253,"about_ca_system_score_gemma":0.0026026217,"threshold_uncertainty_score":0.59806234},"labels":[],"label_agreement":null},{"id":"W2891487475","doi":"10.23889/ijpds.v3i4.997","title":"Point of Care (POC) Influenza Immunization for Pregnant Women, Calgary Zone, Alberta Health Services","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"","keywords":"Medicine; Influenza vaccine; Immunization; Influenza season; Flu season; Pediatrics; Pharmacy; Ambulatory care; Pregnancy; Family medicine; Public health; Cohort; Health care; Vaccination; Environmental health; Nursing; Virology; Immunology; Internal medicine","score_opus":0.08915574594241656,"score_gpt":0.4654501081868341,"score_spread":0.37629436224441754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891487475","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9473248,0.0017924843,0.03891048,0.0031621237,0.0036508888,0.0030068657,0.0016383039,0.000051082916,0.00046296907],"genre_scores_gemma":[0.98001665,0.00020811369,0.016331457,0.001712392,0.0006392612,0.000051607334,0.0008002053,0.000022780687,0.0002175056],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9975033,0.000030118148,0.0006607264,0.00032543275,0.0011100421,0.00037039528],"domain_scores_gemma":[0.9951118,0.00013244299,0.0005115143,0.00047579658,0.0035869386,0.0001815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013760002,0.00011940243,0.00023478296,0.00045832904,0.0005710999,0.00012538089,0.0011242065,0.000036558682,0.000036736834],"category_scores_gemma":[0.0011789434,0.00009698289,0.000053951753,0.00033274898,0.00028202985,0.0016044739,0.00043099292,0.00011044144,0.000005110408],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011390844,0.0012222629,0.41272187,0.0037065027,0.0014014521,0.0000118133285,0.06317889,0.00115937,0.025372736,0.035969034,0.00615029,0.43771493],"study_design_scores_gemma":[0.014171816,0.0063760714,0.5570415,0.005793258,0.00012629316,0.0003413646,0.01102662,0.1264952,0.0074534416,0.003526033,0.26679888,0.00084954133],"about_ca_topic_score_codex":0.0013983505,"about_ca_topic_score_gemma":0.0006478655,"teacher_disagreement_score":0.4368654,"about_ca_system_score_codex":0.0005786028,"about_ca_system_score_gemma":0.00061974296,"threshold_uncertainty_score":0.43924966},"labels":[],"label_agreement":null},{"id":"W2891492978","doi":"10.23889/ijpds.v3i4.763","title":"Methodological issues for measuring pharmacotherapy treatment and its calibration with patient outcomes using real-world data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Discontinuation; Proxy (statistics); Pharmacotherapy; Concordance; Medicine; Ambulatory; Health care; Computer science; Emergency medicine; Data mining; Medical emergency; Machine learning; Internal medicine","score_opus":0.722420015116938,"score_gpt":0.586246670876873,"score_spread":0.136173344240065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891492978","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8533287,0.00011404004,0.13640045,0.007825205,0.0010355738,0.0008570751,0.00034562763,0.000033190827,0.00006014598],"genre_scores_gemma":[0.8547682,0.00022013483,0.1428522,0.0006898595,0.00060413074,0.000018868424,0.00048284652,0.000010954049,0.00035279198],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985767,0.00003581879,0.0003092297,0.0003972566,0.00052817,0.00015283664],"domain_scores_gemma":[0.9985623,0.000113308895,0.00029483353,0.00035593347,0.0005590216,0.00011462661],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008639223,0.00010071903,0.00017085651,0.00017922284,0.00030963842,0.00015274891,0.0005938945,0.000015803318,0.000057779725],"category_scores_gemma":[0.00048559034,0.000065426895,0.000019179506,0.00016957425,0.00013592707,0.0014115174,0.000112664246,0.000049469996,0.0000021829505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036101667,0.0006389624,0.5216532,0.000051855033,0.00059356086,0.000018673994,0.0007026048,0.00027169954,0.053926136,0.007155534,0.005419509,0.40595812],"study_design_scores_gemma":[0.0034677077,0.0012168677,0.09275977,0.00023849795,0.000142562,0.00030386218,0.00016511785,0.8497108,0.00894244,0.0007735997,0.042013325,0.00026542577],"about_ca_topic_score_codex":0.00015080174,"about_ca_topic_score_gemma":0.000082750994,"teacher_disagreement_score":0.84943914,"about_ca_system_score_codex":0.00012746389,"about_ca_system_score_gemma":0.00015911945,"threshold_uncertainty_score":0.26680315},"labels":[],"label_agreement":null},{"id":"W2891497451","doi":"10.23889/ijpds.v3i4.967","title":"Using data to explore vulnerable women's utilization of maternity health care","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Medicine; Socioeconomic status; Poverty; Disadvantaged; Prenatal care; Health care; Environmental health; Nursing; Family medicine; Population; Economic growth","score_opus":0.7668916031732875,"score_gpt":0.6376891343823357,"score_spread":0.12920246879095187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891497451","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9384851,0.000074527095,0.04171645,0.0031267137,0.010732106,0.0010531145,0.0045422525,0.000051789906,0.00021797093],"genre_scores_gemma":[0.96791863,0.000032175503,0.027767863,0.0013989423,0.0011669152,0.000012666798,0.0016270407,0.000014430724,0.00006131103],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99685663,0.00021338656,0.0009536489,0.00047688177,0.0009861689,0.0005132786],"domain_scores_gemma":[0.99566656,0.00012823234,0.00077701,0.00097200094,0.002129252,0.00032691637],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0039682304,0.00011348845,0.0002068822,0.0005096951,0.0030544775,0.00008825385,0.0028632272,0.00006557928,0.00031253183],"category_scores_gemma":[0.0020210685,0.00010977308,0.000019736017,0.0005315084,0.00014659352,0.0027834766,0.0013687022,0.00029251198,0.000034014516],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002341072,0.00072019576,0.55110747,0.0013879536,0.0002570994,0.000007731745,0.21480496,0.005910101,0.0026855003,0.04948422,0.09707198,0.07422172],"study_design_scores_gemma":[0.0037120106,0.0010567995,0.25548008,0.0018890621,0.000055259672,0.00004989607,0.070428945,0.24982144,0.00020209313,0.0064683342,0.40996584,0.0008702323],"about_ca_topic_score_codex":0.0014093405,"about_ca_topic_score_gemma":0.00080455904,"teacher_disagreement_score":0.31289387,"about_ca_system_score_codex":0.0008693932,"about_ca_system_score_gemma":0.0013648601,"threshold_uncertainty_score":0.9982434},"labels":[],"label_agreement":null},{"id":"W2891509389","doi":"10.23889/ijpds.v3i4.989","title":"Canadian trends in the social determinants of health inequalities, a census-mortality linkage approach","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Census; Inequality; Socioeconomic status; Demography; Educational attainment; Geography; Mortality rate; Health equity; American Community Survey; Medicine; Public health; Population; Sociology; Economic growth; Economics; Mathematics","score_opus":0.2919626739586315,"score_gpt":0.5322101699878887,"score_spread":0.2402474960292572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891509389","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9627135,0.00006261558,0.0006550995,0.026840555,0.0038429527,0.00032866982,0.0018314115,0.000011625718,0.003713618],"genre_scores_gemma":[0.9966067,0.000020451756,0.00064798055,0.0016322342,0.00080124184,0.0000036480433,0.00018667924,0.000003206308,0.00009786868],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976201,0.0002319862,0.0005529432,0.00018837542,0.0009905682,0.0004160094],"domain_scores_gemma":[0.9988986,0.00008894817,0.00034248433,0.00018531582,0.00033922857,0.00014539647],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.009488725,0.000060162474,0.00013541864,0.00037636762,0.0015614688,0.00024149874,0.0019579525,0.00004034,0.000039501032],"category_scores_gemma":[0.00080431276,0.000047010122,0.000036732472,0.00053300936,0.0003835787,0.0010013839,0.000075797696,0.00011457375,7.295485e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015043733,0.000067440094,0.790886,0.000019287307,0.000008585985,0.0000023751015,0.022281474,0.000005304215,5.5179856e-7,0.10151229,0.0053638862,0.079837784],"study_design_scores_gemma":[0.00017503869,0.000018766075,0.9579955,0.000025110241,0.0000024488786,0.0000051631446,0.005952664,0.0014458733,4.941984e-7,0.0015112596,0.032804377,0.00006332777],"about_ca_topic_score_codex":0.612626,"about_ca_topic_score_gemma":0.72486144,"teacher_disagreement_score":0.1671095,"about_ca_system_score_codex":0.00053535175,"about_ca_system_score_gemma":0.0015561414,"threshold_uncertainty_score":0.99973834},"labels":[],"label_agreement":null},{"id":"W2891516089","doi":"10.23889/ijpds.v3i4.812","title":"Cross-Sectoral Data Linkage: Tracking Mental Health Service Utilization from Childhood into Adulthood","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Adolescent and Pediatric Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Centre for Addiction and Mental Health; Hospital for Sick Children; Western University; Vanier College; McMaster University; University of Calgary","funders":"","keywords":"Mental health; Medicine; Psychiatry; Population; Anxiety; Christian ministry; Young adult; Depression (economics); Tracking (education); Psychology; Gerontology; Environmental health","score_opus":0.32888419428816,"score_gpt":0.5777957789375597,"score_spread":0.24891158464939972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891516089","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8637849,0.00058632897,0.051828597,0.03408141,0.03229174,0.0017847065,0.015346284,0.00018351835,0.000112486116],"genre_scores_gemma":[0.9516962,0.0001707075,0.010892001,0.005050294,0.009222858,0.0000056713707,0.022876207,0.000027176253,0.000058870606],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99598145,0.0002340921,0.0011289367,0.00077538856,0.001321638,0.000558472],"domain_scores_gemma":[0.9955826,0.00018190901,0.0009920521,0.00099813,0.0018697464,0.00037556692],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0036881994,0.0001731767,0.00020489458,0.0003013979,0.0036442743,0.0003268306,0.0040789135,0.00012478091,0.00045943592],"category_scores_gemma":[0.0016164343,0.00015961823,0.00003141481,0.00057746726,0.00012146801,0.0052304347,0.0013117831,0.00056920067,0.00010676477],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018411753,0.00013089554,0.88696337,0.000062035644,0.000031088504,0.000001568277,0.006874652,0.000014685188,0.00008215593,0.00046354477,0.020150146,0.085041754],"study_design_scores_gemma":[0.0015839445,0.00007888482,0.89185256,0.00037431912,0.000010730924,0.000012138439,0.00095815735,0.03983609,0.000009130353,0.0010945286,0.06397426,0.00021526142],"about_ca_topic_score_codex":0.004146172,"about_ca_topic_score_gemma":0.0045043644,"teacher_disagreement_score":0.087911285,"about_ca_system_score_codex":0.0005470411,"about_ca_system_score_gemma":0.001837993,"threshold_uncertainty_score":0.9976528},"labels":[],"label_agreement":null},{"id":"W2891521002","doi":"10.23889/ijpds.v3i4.942","title":"Data Linkage Methods in Manitoba","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health","funders":"","keywords":"Linkage (software); Computer science; Record linkage; Linked data; Data quality; Population; Data mining; Process (computing); Data science; Information retrieval; Engineering; Medicine","score_opus":0.6645466192572466,"score_gpt":0.6439882190382802,"score_spread":0.020558400218966377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891521002","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019570952,0.00003188883,0.95660466,0.006056309,0.012693381,0.00030517127,0.0027872748,0.000026689275,0.0019236808],"genre_scores_gemma":[0.44365615,0.00005367993,0.54883873,0.0019924208,0.0024093932,0.0000059508343,0.0021113534,0.000014152693,0.000918191],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99494386,0.00022445882,0.0010192628,0.0008845409,0.0026463016,0.00028159932],"domain_scores_gemma":[0.9950602,0.00077886536,0.00053385034,0.0024548373,0.0010367021,0.00013554942],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.035995662,0.00010131513,0.00015463275,0.0009385216,0.00041187712,0.0020717562,0.017893728,0.00003482069,0.00026793563],"category_scores_gemma":[0.020748938,0.000079724836,0.00003058222,0.0010037804,0.00032952937,0.010158585,0.0048686434,0.00015824789,0.00015192274],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008785813,0.00012963923,0.021011217,0.0000024793592,0.000025295722,0.000014231434,0.00018019663,0.000114252056,0.0006028654,0.03899502,0.07518413,0.8636528],"study_design_scores_gemma":[0.00046077304,0.000043609954,0.11673082,0.000030076348,0.000007741967,0.000044946726,0.00053167716,0.14896795,0.00008239586,0.07559175,0.6573492,0.00015903173],"about_ca_topic_score_codex":0.00036373505,"about_ca_topic_score_gemma":0.0036317029,"teacher_disagreement_score":0.8634938,"about_ca_system_score_codex":0.00013339466,"about_ca_system_score_gemma":0.00016223347,"threshold_uncertainty_score":0.9989642},"labels":[],"label_agreement":null},{"id":"W2891541079","doi":"10.23889/ijpds.v3i4.811","title":"Developing a Primary Care EMR-based Frailty Definition using Machine Learning","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Frailty in Older Adults","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health; Alberta Health Services; University of Calgary","funders":"","keywords":"CHAID; Medicine; Medical diagnosis; Machine learning; Artificial intelligence; Computer science; Decision tree","score_opus":0.2091686129472483,"score_gpt":0.4263055596183748,"score_spread":0.21713694667112649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891541079","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6842256,0.00011367298,0.30910927,0.0020330965,0.0032722787,0.00035163236,0.00030114074,0.00007886916,0.00051442574],"genre_scores_gemma":[0.7980637,0.000009360599,0.19829902,0.00074095314,0.0007524096,0.000002536659,0.0020768575,0.000015040555,0.00004011346],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978878,0.000028270779,0.00040060605,0.00036110374,0.0010791025,0.0002431146],"domain_scores_gemma":[0.99758536,0.00007457848,0.0002912154,0.00028580052,0.0016361593,0.00012687889],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007213293,0.00011893469,0.00013608033,0.00043271406,0.0006486162,0.0002490779,0.000772984,0.00004723397,0.00005907031],"category_scores_gemma":[0.0013706853,0.00011012433,0.00004859229,0.00032757397,0.00019711495,0.001479224,0.00021976873,0.0002259919,0.000013657151],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014341043,0.00023526914,0.76065445,0.00028377862,0.00019604394,0.00010536342,0.0014803293,0.0024682381,0.067694604,0.006610497,0.0007165862,0.15812075],"study_design_scores_gemma":[0.0060800645,0.00062855816,0.38652423,0.0021027282,0.00015062698,0.0018579203,0.0003737689,0.55941033,0.008760266,0.002605687,0.030826299,0.00067951356],"about_ca_topic_score_codex":0.00019359944,"about_ca_topic_score_gemma":0.00010379718,"teacher_disagreement_score":0.5569421,"about_ca_system_score_codex":0.0008950483,"about_ca_system_score_gemma":0.0007943046,"threshold_uncertainty_score":0.4988697},"labels":[],"label_agreement":null},{"id":"W2891566313","doi":"10.23889/ijpds.v3i4.749","title":"Ligo: An Open Source Application for the Management and Execution of Administrative Data Linkage","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Python (programming language); Probabilistic logic; Population; Plug-in; Cloud computing; Interface (matter); Data science; Data mining; Software engineering; Programming language; Artificial intelligence; Operating system","score_opus":0.5482114767746085,"score_gpt":0.5869358928333936,"score_spread":0.03872441605878518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891566313","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010324895,0.000024192748,0.9814712,0.0034568012,0.0011489815,0.0011216017,0.002103249,0.000009262646,0.00033984956],"genre_scores_gemma":[0.9460676,0.00005021004,0.050721638,0.00045302272,0.00046770246,0.000035628873,0.0015536112,0.000006916757,0.00064370886],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969812,0.000066600725,0.00067164685,0.00067866244,0.0014519218,0.00014995097],"domain_scores_gemma":[0.99592507,0.0004894604,0.0007206667,0.0017814897,0.0009963817,0.00008693464],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.013581698,0.00008447292,0.00011711746,0.00022636124,0.0007726824,0.0017512917,0.013022207,0.000023124698,0.000025575648],"category_scores_gemma":[0.0017841994,0.000056724497,0.000017927723,0.00037256454,0.00041183844,0.006958404,0.004108595,0.00005764216,0.000006142339],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003345218,0.00016796443,0.0014660647,0.000009551729,0.00009520943,5.1345097e-7,0.00046655745,0.00014295852,0.00040445087,0.20476663,0.018260675,0.7738849],"study_design_scores_gemma":[0.0007922654,0.0002694346,0.048441637,0.00003466881,0.00006075424,0.000019844183,0.002196851,0.3438808,0.00021227643,0.0657056,0.53823304,0.00015283287],"about_ca_topic_score_codex":0.0001653313,"about_ca_topic_score_gemma":0.00035166895,"teacher_disagreement_score":0.9357427,"about_ca_system_score_codex":0.000040015933,"about_ca_system_score_gemma":0.00008484885,"threshold_uncertainty_score":0.999285},"labels":[],"label_agreement":null},{"id":"W2891574108","doi":"10.23889/ijpds.v3i4.655","title":"Utilizing population-based clinical and administrative data to explore the relevance of frailty to cholinesterase inhibitor use and discontinuation at nursing home transition.","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Frailty in Older Adults","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; University of Ottawa; Institute for Clinical Evaluative Sciences; University of Calgary; Sunnybrook Hospital; University of Waterloo","funders":"","keywords":"Discontinuation; Medicine; Hazard ratio; Dementia; Confidence interval; Incidence (geometry); Population; Emergency medicine; Gerontology; Disease; Internal medicine; Environmental health","score_opus":0.3813249375052175,"score_gpt":0.5029470447739692,"score_spread":0.12162210726875172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891574108","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96597403,0.000020174135,0.019900698,0.011652048,0.001071638,0.00055042544,0.00081333175,0.000012344213,0.000005318486],"genre_scores_gemma":[0.9717232,0.000012777513,0.025583863,0.00089502265,0.00071656203,0.0000062821355,0.0010186613,0.000011271344,0.000032345124],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977658,0.000058258982,0.0006904345,0.0005351366,0.0007827997,0.0001676128],"domain_scores_gemma":[0.99750644,0.00045190225,0.0002867619,0.0006556059,0.0008589794,0.00024029589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013659477,0.000120470744,0.00018452475,0.00022400057,0.00039655523,0.0002621617,0.0006993718,0.000041510884,0.000011223161],"category_scores_gemma":[0.005154763,0.000091739385,0.000026736785,0.0002801816,0.00039949542,0.0024706821,0.00024319332,0.0001344255,0.0000017767344],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0039820666,0.00052889704,0.8060645,0.000045622204,0.00010601425,0.000015370366,0.005495677,0.0004633628,0.01119369,0.0008952848,0.005524528,0.16568498],"study_design_scores_gemma":[0.0012480828,0.00036512682,0.9454192,0.00073024107,0.000048569178,0.00011341066,0.00030228557,0.049810205,0.0004653283,0.00021023766,0.0011603406,0.00012698551],"about_ca_topic_score_codex":0.0000944884,"about_ca_topic_score_gemma":0.0003049205,"teacher_disagreement_score":0.165558,"about_ca_system_score_codex":0.000108844295,"about_ca_system_score_gemma":0.00014607729,"threshold_uncertainty_score":0.6171105},"labels":[],"label_agreement":null},{"id":"W2891577755","doi":"10.23889/ijpds.v3i4.692","title":"International Journal Population Data Science: development and future directions","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"Economic and Social Research Council; Medical Research Council","keywords":"Viewpoints; Publication; Session (web analytics); Publishing; Presentation (obstetrics); Population; Public relations; Scope (computer science); Data science; Computer science; Political science; World Wide Web; Sociology","score_opus":0.13969425561633755,"score_gpt":0.48500060827371094,"score_spread":0.3453063526573734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891577755","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84659654,0.0004537259,0.015626268,0.06609243,0.067124516,0.0010432656,0.000873453,0.00012617215,0.00206365],"genre_scores_gemma":[0.9374359,0.000570167,0.042926017,0.0009963737,0.016456043,0.0000054599386,0.001400588,0.000020315374,0.0001891182],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99522424,0.00005172159,0.0009352629,0.0006874737,0.0026481994,0.00045311823],"domain_scores_gemma":[0.9943256,0.000054240012,0.00056000846,0.0007089325,0.0036708596,0.00068038586],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007455579,0.00015894523,0.00020431454,0.001175943,0.0019769347,0.0013191703,0.002780861,0.00007934836,0.00011837963],"category_scores_gemma":[0.001929554,0.00013038977,0.000031109124,0.0007003566,0.00039225823,0.0069191274,0.00083815516,0.0003765879,0.000012171255],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015675536,0.00011927861,0.09659942,0.000019079183,0.00008480884,0.00001983039,0.00088744116,0.0000025752026,0.00030750484,0.00538086,0.0047214436,0.891701],"study_design_scores_gemma":[0.00064108166,0.00007525245,0.36216313,0.00010416104,0.000011683609,0.0021592833,0.00024645374,0.0074749915,0.000020473924,0.00021681878,0.6267686,0.00011810584],"about_ca_topic_score_codex":0.00074658333,"about_ca_topic_score_gemma":0.00032923912,"teacher_disagreement_score":0.8915829,"about_ca_system_score_codex":0.00087916106,"about_ca_system_score_gemma":0.0034272235,"threshold_uncertainty_score":0.99971753},"labels":[],"label_agreement":null},{"id":"W2891601420","doi":"10.23889/ijpds.v3i4.984","title":"Pan-Canadian Real-World Health Data Network: Building a National Data Platform","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information; University of New Brunswick; University of Manitoba; Institute for Clinical Evaluative Sciences; University of British Columbia; Vector Institute; Manitoba Health","funders":"","keywords":"Computer science; Data science; Work (physics); Construct (python library); Population; Social network analysis; World Wide Web; Medicine; Engineering; Environmental health","score_opus":0.5271371237842121,"score_gpt":0.5504790915676688,"score_spread":0.023341967783456763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891601420","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06391101,0.00037535388,0.7989773,0.047943443,0.042972498,0.0015366541,0.03264941,0.00023224135,0.01140209],"genre_scores_gemma":[0.91070485,0.00014773477,0.07560089,0.0017563843,0.0034620925,0.0000032945118,0.007954625,0.000018884632,0.00035124918],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99120474,0.0000928443,0.0014823922,0.0014373746,0.0050900606,0.0006926054],"domain_scores_gemma":[0.99163955,0.00070738274,0.0011301725,0.0029476555,0.0030495333,0.00052569085],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.030591326,0.00018419753,0.00024758518,0.001656571,0.0021312844,0.0027835502,0.018607521,0.000054871456,0.00020778563],"category_scores_gemma":[0.008898316,0.00015585257,0.000046640933,0.0020617226,0.0003423806,0.012557163,0.0027006092,0.00025286802,0.00008239184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013406533,0.000083324405,0.04636052,0.000004013211,0.00009455685,0.000007076221,0.00020948028,0.005181252,0.000054887118,0.107244045,0.4276378,0.412989],"study_design_scores_gemma":[0.0002919612,0.000035334106,0.04166568,0.000051368846,0.000008178109,0.000059505463,0.00009480495,0.709823,0.0000011921263,0.05850388,0.18930036,0.00016471412],"about_ca_topic_score_codex":0.026290895,"about_ca_topic_score_gemma":0.23095642,"teacher_disagreement_score":0.84679383,"about_ca_system_score_codex":0.00044380277,"about_ca_system_score_gemma":0.00281815,"threshold_uncertainty_score":0.99945015},"labels":[],"label_agreement":null},{"id":"W2891602270","doi":"10.23889/ijpds.v3i4.607","title":"Avoidable mortality among parents whose children were placed in care in Sweden: A retrospective matched cohort study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Family Support in Illness","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Medicine; Hazard ratio; Cohort; Pediatrics; Demography; Child mortality; Mortality rate; Retrospective cohort study; Cohort study; Health care; Population; Confidence interval; Environmental health","score_opus":0.05214947706074678,"score_gpt":0.4141771366373266,"score_spread":0.3620276595765798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891602270","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946026,0.000010144301,0.000106512765,0.00014203176,0.002811389,0.0011490971,0.00024280447,0.000024453466,0.0009109498],"genre_scores_gemma":[0.9988326,0.0000100197385,0.00028422283,0.000047670852,0.00046677975,0.00003759205,0.00021667183,0.000010276991,0.000094199684],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9960965,0.0001743059,0.00061373616,0.00063603505,0.002060734,0.0004186996],"domain_scores_gemma":[0.99809587,0.00006733496,0.00037478394,0.00044847588,0.00086494733,0.00014860036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049157445,0.00013439092,0.0002186388,0.0004926459,0.00075788,0.0006031983,0.0026463508,0.00007014596,0.000103964594],"category_scores_gemma":[0.0018873267,0.00013463329,0.000036965695,0.0008282832,0.00049759226,0.0039667017,0.00041888133,0.00026228034,0.000010507642],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047159705,0.0001401837,0.99246347,0.0000010097119,0.000019848228,0.000008655595,0.0063596736,0.00008726367,0.000009995077,0.00035182066,0.00015643355,0.00035448463],"study_design_scores_gemma":[0.00078766,0.000059892915,0.98582995,0.000051695148,0.000009510675,0.0000033939625,0.011175909,0.00092845975,0.000011106922,0.00088837335,0.00009432281,0.00015973028],"about_ca_topic_score_codex":0.037915893,"about_ca_topic_score_gemma":0.18018132,"teacher_disagreement_score":0.14226544,"about_ca_system_score_codex":0.0015256322,"about_ca_system_score_gemma":0.0005078049,"threshold_uncertainty_score":0.9684907},"labels":[],"label_agreement":null},{"id":"W2891609209","doi":"10.23889/ijpds.v3i4.815","title":"The association between maternal and offspring preterm birth. Results from a sibling design","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Preterm Birth and Chorioamnionitis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Offspring; Singleton; Medicine; Sibling; Confounding; Confidence interval; Gestation; Relative risk; Obstetrics; Cohort study; Pregnancy; Premature birth; Pediatrics; Demography; Internal medicine; Developmental psychology; Psychology; Biology; Genetics","score_opus":0.0793174747031573,"score_gpt":0.36850403042590874,"score_spread":0.2891865557227514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891609209","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9755765,0.00005436333,0.019145472,0.0020398372,0.0021242986,0.00021705106,0.0006654827,0.00002581889,0.00015116742],"genre_scores_gemma":[0.98862517,0.00013752622,0.008613358,0.00012110211,0.0021611426,0.000002759303,0.00016456572,0.0000076038805,0.00016677163],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99814606,0.000036172365,0.00041531306,0.00029299158,0.0008859875,0.00022349849],"domain_scores_gemma":[0.9981216,0.00042362575,0.00040356387,0.00027701602,0.0006311373,0.00014303562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022106688,0.00008199967,0.00010013467,0.00016101579,0.0007146036,0.0007578317,0.00076065323,0.000042725624,0.000008380761],"category_scores_gemma":[0.0027246939,0.000059551054,0.000027967008,0.0001391597,0.00012171103,0.0012536609,0.00022234728,0.00014633812,0.000006484813],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008318044,0.000010081229,0.890623,0.0000033175909,0.000135795,0.0000069642506,0.00022393222,0.000012629424,0.0025957408,0.00026959254,0.00095261016,0.10433456],"study_design_scores_gemma":[0.0015112265,0.0001231641,0.96112233,0.00013508186,0.00004436722,0.0000684411,0.0000262836,0.022393512,0.0023095729,0.0023337547,0.009836496,0.00009573738],"about_ca_topic_score_codex":0.00016496483,"about_ca_topic_score_gemma":0.000038335664,"teacher_disagreement_score":0.10423883,"about_ca_system_score_codex":0.00020060845,"about_ca_system_score_gemma":0.00012891558,"threshold_uncertainty_score":0.7307788},"labels":[],"label_agreement":null},{"id":"W2891628242","doi":"10.23889/ijpds.v3i4.714","title":"Harnessing the Power of Administrative Data to Create a Provincial-Level Child Heath Profile and Birth Cohort in New Brunswick (NB) and Prince Edward Island (PEI)","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick; Dalhousie University; University of Prince Edward Island; Université de Moncton","funders":"","keywords":"Custodians; Government (linguistics); Cohort; Work (physics); Outreach; Population; Medicine; Business; Environmental health; Engineering; Geography; Political science","score_opus":0.0778604364466735,"score_gpt":0.375717504103884,"score_spread":0.2978570676572105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891628242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9823671,0.000020598138,0.01258409,0.0029082356,0.00026324592,0.0007240508,0.0005413736,0.000005502249,0.0005858104],"genre_scores_gemma":[0.99047583,0.000035056928,0.008668767,0.00041435083,0.00013040728,0.0000035642588,0.00007842888,0.000008042233,0.00018553776],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979214,0.000055357857,0.00039330486,0.00064566376,0.00074083766,0.00024344225],"domain_scores_gemma":[0.9989064,0.000096148106,0.00026845117,0.0004949044,0.00005228292,0.00018182154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024083976,0.00011537516,0.0001246867,0.00011652355,0.00041339008,0.00021470505,0.0013376919,0.000027530412,0.00013782381],"category_scores_gemma":[0.0010268629,0.00008725667,0.000009783403,0.00024748273,0.0005329451,0.0023011544,0.0013427293,0.00015425905,0.000007357243],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009342779,0.000044305343,0.97799957,0.000003787717,0.000010176618,0.0000032810585,0.0009131474,0.000036423633,0.0008548437,0.00024107007,0.00038151196,0.019418444],"study_design_scores_gemma":[0.00034621116,0.00009868492,0.98563844,0.00009470567,0.0000069795146,0.00008578344,0.00014273846,0.008192721,0.00027032697,0.00024154359,0.0047745775,0.00010731353],"about_ca_topic_score_codex":0.0030233716,"about_ca_topic_score_gemma":0.010753935,"teacher_disagreement_score":0.019311132,"about_ca_system_score_codex":0.0001599469,"about_ca_system_score_gemma":0.00033527362,"threshold_uncertainty_score":0.60009485},"labels":[],"label_agreement":null},{"id":"W2891639455","doi":"10.23889/ijpds.v3i4.636","title":"The Overlap Between the Child Welfare and Youth Justice Systems in Manitoba, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child Abuse and Trauma","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Cohort; Welfare; Medicine; Social Welfare; Foster care; Demography; Economic Justice; Psychiatry; Population; Cohort study; Criminal justice; Gerontology; Psychology; Environmental health; Political science; Criminology; Sociology; Nursing; Law","score_opus":0.07640942307490207,"score_gpt":0.3560602702963534,"score_spread":0.27965084722145134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891639455","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96729964,0.00048039106,0.00040723677,0.011135995,0.015545255,0.0003803963,0.0011676722,0.000011156754,0.0035722794],"genre_scores_gemma":[0.99801475,0.000017182178,0.000020515676,0.00019149786,0.0016079864,0.000002765393,0.0000846048,0.000005083126,0.000055621447],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99871635,0.000042161213,0.00028273326,0.00022072562,0.0005440253,0.00019399828],"domain_scores_gemma":[0.9990837,0.00014411069,0.00017502239,0.00032941473,0.00020898461,0.000058774494],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0010918186,0.000068706315,0.00006319372,0.00007695673,0.0013517215,0.00042817436,0.0015319326,0.000020789625,0.000015792382],"category_scores_gemma":[0.0002259808,0.00004052455,0.000012525241,0.00015922077,0.00019139856,0.00050484366,0.0001666491,0.00016042785,0.000004266191],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021279794,0.00005636718,0.69319355,0.000008319957,0.00019382985,0.000020532354,0.0026205736,0.00015389826,0.0000057060165,0.22732945,0.009995074,0.06620988],"study_design_scores_gemma":[0.0003478702,0.000019001065,0.94130856,0.000032910008,0.000023282651,0.00011201699,0.0033127938,0.0009067608,0.0000012351373,0.00018296597,0.053687345,0.000065267835],"about_ca_topic_score_codex":0.24533156,"about_ca_topic_score_gemma":0.46693105,"teacher_disagreement_score":0.24811499,"about_ca_system_score_codex":0.000120352146,"about_ca_system_score_gemma":0.00007380572,"threshold_uncertainty_score":0.9999484},"labels":[],"label_agreement":null},{"id":"W2891644085","doi":"10.23889/ijpds.v3i4.616","title":"Factors associated with the breast cancer diagnostic interval across five Canadian provinces: a CanIMPACT study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; Nova Scotia Health Authority; Dalhousie University; University of Toronto; CARE Canada; Queen's University; CancerCare Manitoba; BC Cancer Agency","funders":"","keywords":"Medicine; Percentile; Socioeconomic status; Breast cancer; Referral; Cancer; Demography; Population; Confidence interval; Cancer registry; Pediatrics; Family medicine; Internal medicine; Environmental health","score_opus":0.18808635573983426,"score_gpt":0.4608237658240084,"score_spread":0.2727374100841742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891644085","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99283725,0.00001903076,0.00019433518,0.003150528,0.0009715185,0.00045156744,0.0023058783,0.000013909155,0.00005595641],"genre_scores_gemma":[0.99853057,0.000003312942,0.000037164315,0.00054591557,0.0005902917,0.000012747707,0.00017221963,0.000009478155,0.00009832073],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99791384,0.00003038407,0.0002504632,0.00031320233,0.0011109738,0.00038111812],"domain_scores_gemma":[0.99753636,0.00016053919,0.00025058215,0.00028360673,0.0014710817,0.00029780282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011382694,0.00012580697,0.00014058307,0.00013924435,0.0008656044,0.00048000613,0.0013038369,0.000027514809,0.00009744816],"category_scores_gemma":[0.0018537586,0.00007014021,0.000035804213,0.00039893124,0.00029894995,0.0014100529,0.00015186516,0.00018756492,0.0000028544755],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012543699,0.00004739459,0.9921449,0.0000010213009,0.00011436553,0.000018806972,0.0016972403,0.000088607616,0.000020183566,0.000022493256,0.0021604614,0.0035590797],"study_design_scores_gemma":[0.00064460345,0.0003653716,0.98970455,0.00018938385,0.000057952482,0.0001162861,0.0049252547,0.0032888297,0.000012521744,0.000020986514,0.0005769847,0.00009729652],"about_ca_topic_score_codex":0.23087756,"about_ca_topic_score_gemma":0.73454404,"teacher_disagreement_score":0.50366646,"about_ca_system_score_codex":0.0013103232,"about_ca_system_score_gemma":0.0014637391,"threshold_uncertainty_score":0.77424407},"labels":[],"label_agreement":null},{"id":"W2891673601","doi":"10.23889/ijpds.v3i4.1008","title":"Linking Emergency Medical Services and Health System Data: Optimal Strategy and Bias Mitigation","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"","keywords":"Psychological intervention; Medical emergency; Linkage (software); Critically ill; Identifier; Medicine; Emergency medical services; Fiscal year; Emergency department; Sample (material); Health care; Emergency medicine; Computer science; Business; Nursing; Intensive care medicine; Finance","score_opus":0.15701790324438844,"score_gpt":0.4566833894850185,"score_spread":0.29966548624063005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891673601","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.961243,0.0028609172,0.013055534,0.013984229,0.0071349004,0.0004160254,0.00081029633,0.000059939925,0.000435181],"genre_scores_gemma":[0.991315,0.0017025166,0.003950227,0.00029538313,0.0016875134,0.0000018372925,0.0010053244,0.0000065674335,0.000035620473],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99802893,0.000021725165,0.00046590317,0.0003828914,0.00092563726,0.00017491414],"domain_scores_gemma":[0.9985825,0.000026111724,0.0002655111,0.0002812742,0.00063839194,0.00020622436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022166048,0.00008927122,0.00013921793,0.0001653596,0.00059322076,0.00012853992,0.00072200637,0.000035739267,0.000030367491],"category_scores_gemma":[0.00029554416,0.00007137093,0.00001439416,0.00016230004,0.00017908232,0.0018478279,0.0005498249,0.0001168237,0.0000017306878],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021766113,0.00011924274,0.74976087,0.000640209,0.00030593018,0.000040938747,0.0014391745,0.00003034277,0.00055496045,0.024264548,0.012706575,0.20991957],"study_design_scores_gemma":[0.001861957,0.00063854776,0.55344486,0.0020616632,0.000110446446,0.002275572,0.003155342,0.40506443,0.00007437436,0.00084287435,0.030123357,0.0003465598],"about_ca_topic_score_codex":0.00022409573,"about_ca_topic_score_gemma":0.00029080428,"teacher_disagreement_score":0.4050341,"about_ca_system_score_codex":0.00006221257,"about_ca_system_score_gemma":0.00021155656,"threshold_uncertainty_score":0.45626345},"labels":[],"label_agreement":null},{"id":"W2891676169","doi":"10.23889/ijpds.v3i4.897","title":"Neighbourhood built environments as correlates of hospital burden and premature mortality in Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada; McGill University","funders":"","keywords":"Medicine; Socioeconomic status; Neighbourhood (mathematics); Environmental health; Type 2 diabetes; Demography; Population; Cohort; Gerontology; Health care; Diabetes mellitus","score_opus":0.035524772104230475,"score_gpt":0.36089281938024215,"score_spread":0.32536804727601165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891676169","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99695086,0.00004857927,0.00018539943,0.00092677894,0.0010777373,0.00018798001,0.00012764681,0.0000026794871,0.0004923193],"genre_scores_gemma":[0.9991185,0.000039328927,0.00031634772,0.000055261564,0.00025157325,0.0000017544759,0.00014845937,0.0000040384416,0.000064741565],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99865586,0.000007496655,0.00026887518,0.00021194694,0.00073052355,0.00012532933],"domain_scores_gemma":[0.99936694,0.00002440519,0.0001874171,0.00022665341,0.00010744093,0.000087149034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030129027,0.000065465676,0.0000975827,0.00011452216,0.000065842025,0.000063681226,0.00049433985,0.000015934087,0.00012617509],"category_scores_gemma":[0.00035770668,0.00005751863,0.000014289134,0.0001011697,0.00015469456,0.0008462353,0.00023047124,0.00007567022,0.0000013887934],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007657844,0.000049528073,0.9920853,0.00001697886,0.000062077284,0.000023633207,0.00010202179,0.00014484936,0.0002734818,0.0023097831,0.00048375517,0.004372034],"study_design_scores_gemma":[0.0006598768,0.00008882419,0.98320323,0.00009685639,0.000028150047,0.000028269385,0.00022285352,0.01331315,0.000068097215,0.0015204218,0.00071181165,0.000058439273],"about_ca_topic_score_codex":0.18198386,"about_ca_topic_score_gemma":0.092225,"teacher_disagreement_score":0.08975886,"about_ca_system_score_codex":0.00036364893,"about_ca_system_score_gemma":0.00069436734,"threshold_uncertainty_score":0.92433953},"labels":[],"label_agreement":null},{"id":"W2891679559","doi":"10.23889/ijpds.v3i4.602","title":"Monitoring health service use at the end of life in the Calgary Zone of Alberta: a Population-level analysis linking multiple administrative datasets","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Palliative Care and End-of-Life Issues","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"","keywords":"Palliative care; End-of-life care; Population; Medicine; Dashboard; Health care; Gerontology; Geography; Demography; Environmental health; Nursing; Database; Economic growth","score_opus":0.4059867998868907,"score_gpt":0.5226946928467824,"score_spread":0.1167078929598917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891679559","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99148417,0.0001585469,0.004382153,0.0018807654,0.0003969513,0.00022486593,0.0014580027,0.0000021132093,0.000012461259],"genre_scores_gemma":[0.9897116,0.000092366994,0.007499413,0.00026470268,0.00022163485,0.0000033444278,0.0021840022,0.00000447747,0.000018477334],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99783516,0.00008456088,0.0007388324,0.00022116322,0.0009759973,0.00014426836],"domain_scores_gemma":[0.9970287,0.0008593954,0.00082624826,0.0004464005,0.00076560443,0.00007362271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016177201,0.00008837254,0.00025231426,0.00033263018,0.00019983541,0.000046870697,0.0009174932,0.000027971846,0.000019359732],"category_scores_gemma":[0.0025439085,0.0000559169,0.0000642312,0.00090160343,0.00020128723,0.00088059297,0.00020444285,0.00011775333,6.902454e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017853534,0.000068570735,0.9942813,0.000020285725,0.00014627658,0.0000011327103,0.0021687879,0.0003705365,0.0003594678,0.00019777783,0.00009734645,0.0021100056],"study_design_scores_gemma":[0.00057839835,0.000084702704,0.9727019,0.0004138781,0.00008623498,0.0000141328765,0.0007068258,0.02391753,0.00053381594,0.00005391299,0.0008552696,0.000053396307],"about_ca_topic_score_codex":0.023794632,"about_ca_topic_score_gemma":0.025160037,"teacher_disagreement_score":0.023546994,"about_ca_system_score_codex":0.00013333594,"about_ca_system_score_gemma":0.00025935794,"threshold_uncertainty_score":0.9926283},"labels":[],"label_agreement":null},{"id":"W2891689890","doi":"10.23889/ijpds.v3i4.637","title":"Trends in systematic recording errors of blood pressure and association with outcomes in Canadian and UK primary care data: a retrospective observational study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Blood Pressure and Hypertension Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Blood pressure; Observational study; Medicine; Retrospective cohort study; Logistic regression; Odds; Odds ratio; Electronic medical record; Emergency medicine; Stroke (engine); Internal medicine; Demography; Engineering","score_opus":0.11472740456641924,"score_gpt":0.3820352428372806,"score_spread":0.26730783827086135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891689890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99680233,0.0006756609,0.0000126359,0.0011807833,0.00033316924,0.0004309354,0.0004740737,0.000004081212,0.00008630519],"genre_scores_gemma":[0.9982879,0.000017897828,0.0011594391,0.00012583264,0.00007862265,0.0000066838184,0.00024509782,0.0000047833264,0.00007369808],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984228,0.0000364004,0.00039478645,0.00030801748,0.0006925138,0.00014549433],"domain_scores_gemma":[0.998471,0.00010865636,0.0002936759,0.00025367405,0.0007963637,0.000076606746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015295449,0.00008093725,0.00033075613,0.0006542567,0.00014393116,0.00007766009,0.00034202865,0.000032274766,0.000005010611],"category_scores_gemma":[0.0009384419,0.000060469996,0.000010414924,0.00032436522,0.000068500434,0.0009934667,0.000193196,0.000115348616,9.0606726e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051866038,0.000050951814,0.9983762,0.00010068906,0.0002586062,0.000007992639,0.00075618055,0.0000040888153,0.000038337937,0.00006244716,0.00010710538,0.00018554948],"study_design_scores_gemma":[0.0013627604,0.00018135217,0.99477214,0.0006530745,0.0005360012,0.000051105275,0.0007829129,0.0014893019,0.000004120438,0.000044858425,0.00006068869,0.00006167567],"about_ca_topic_score_codex":0.027285337,"about_ca_topic_score_gemma":0.21056867,"teacher_disagreement_score":0.18328333,"about_ca_system_score_codex":0.00009573706,"about_ca_system_score_gemma":0.00021830431,"threshold_uncertainty_score":0.9791921},"labels":[],"label_agreement":null},{"id":"W2891693278","doi":"10.23889/ijpds.v3i4.974","title":"Does the family physicians’ characteristics affect Cervical Cancer Screening rates?","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cervical Cancer and HPV Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Graduation (instrument); Family medicine; Medicine; Certification; Test (biology); Guideline; Affect (linguistics); Cancer screening; Cancer; Psychology; Internal medicine","score_opus":0.12465348269587284,"score_gpt":0.48181753162619645,"score_spread":0.3571640489303236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891693278","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8947535,0.00019920549,0.046866998,0.04019491,0.013860262,0.0009749823,0.0014217423,0.000066687666,0.0016617216],"genre_scores_gemma":[0.9912532,0.00009819416,0.0012101267,0.0019729056,0.0049855765,0.000011345425,0.00019287142,0.00001034484,0.0002654133],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9978959,0.000026908729,0.00027537925,0.00029498737,0.0012403119,0.00026652307],"domain_scores_gemma":[0.9978148,0.00011759745,0.00015350993,0.0003494464,0.0014353802,0.0001292655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001088624,0.00008865768,0.00012739298,0.00014063192,0.0005781212,0.00039779482,0.0012913068,0.00002875909,0.00056546193],"category_scores_gemma":[0.00068378047,0.00004503933,0.000056308465,0.00030941932,0.0003733753,0.00087180233,0.00032610542,0.00023847965,0.000014386231],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087079074,0.000092483344,0.20266762,0.000021232396,0.00010543844,0.000010549629,0.00019516867,0.000014390428,0.0053455257,0.0013917359,0.007050451,0.7822346],"study_design_scores_gemma":[0.0005461936,0.00009179421,0.9316499,0.000059747916,0.00002726314,0.00002802627,0.000074437594,0.03483247,0.00041346098,0.00034115452,0.031859368,0.00007614131],"about_ca_topic_score_codex":0.00034602085,"about_ca_topic_score_gemma":0.00015613918,"teacher_disagreement_score":0.78215843,"about_ca_system_score_codex":0.00014753416,"about_ca_system_score_gemma":0.00022842178,"threshold_uncertainty_score":0.61914116},"labels":[],"label_agreement":null},{"id":"W2891695662","doi":"10.23889/ijpds.v3i4.642","title":"Using Large Data to Present Uncertainty for Risk Prediction in the Era of Precision Medicine: The RESPECT Algorithm for Predicted Death at End-of-Life","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Palliative Care and End-of-Life Issues","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ottawa Public Health; Ottawa Hospital; Bruyère; University of Ottawa; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Percentile; Medicine; Hazard ratio; Proportional hazards model; Survival analysis; End-of-life care; Palliative care; Hazard; Demography; Gerontology; Statistics; Mathematics; Confidence interval; Internal medicine; Nursing","score_opus":0.37372098600163445,"score_gpt":0.5315147271103281,"score_spread":0.15779374110869365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891695662","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4062821,0.00035025485,0.5698369,0.0028428682,0.0019184479,0.0018630439,0.016859015,0.000008668638,0.00003869314],"genre_scores_gemma":[0.916522,0.00021673742,0.07846167,0.00020988833,0.0019060175,0.000027842292,0.0026094627,0.000013056175,0.000033306333],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973179,0.00008305103,0.0008085345,0.00034794022,0.0012405888,0.00020198368],"domain_scores_gemma":[0.99572057,0.0011638509,0.0006818844,0.00074199174,0.0016078709,0.00008382181],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0052467203,0.00010509408,0.00023466947,0.00025857612,0.00027898126,0.000030073483,0.0018514268,0.00004266904,0.000026830516],"category_scores_gemma":[0.01038971,0.000059810907,0.000056185774,0.00039493234,0.000256732,0.0006617499,0.00040883388,0.00013030053,2.5437694e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011331205,0.0009954949,0.6310209,0.00023102509,0.00080534397,0.0000049844493,0.013330434,0.0075343894,0.014213932,0.005497238,0.07678921,0.23824582],"study_design_scores_gemma":[0.0027519239,0.0007577851,0.097846076,0.0009568024,0.00014264855,0.00002609274,0.0007015442,0.8477033,0.00090173824,0.0011508119,0.046986923,0.00007435003],"about_ca_topic_score_codex":0.00066415756,"about_ca_topic_score_gemma":0.00028216303,"teacher_disagreement_score":0.8401689,"about_ca_system_score_codex":0.00017010917,"about_ca_system_score_gemma":0.00030024428,"threshold_uncertainty_score":0.9979462},"labels":[],"label_agreement":null},{"id":"W2891698248","doi":"10.23889/ijpds.v3i4.1032","title":"Identify Patients with Congestive Heart Failure through Analyzing Free-Text Clinical Notes","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning; Random forest; Natural language processing; Chart; Text messaging; Heart failure; Data mining; Medicine; Internal medicine; World Wide Web","score_opus":0.0871701148940806,"score_gpt":0.4621158678193725,"score_spread":0.37494575292529186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891698248","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3479741,0.000018820865,0.6342196,0.01204933,0.005175418,0.00028183003,0.00015374753,0.00007719164,0.000049965693],"genre_scores_gemma":[0.7852827,0.000003440951,0.21314412,0.0006214199,0.00081238925,0.0000029742844,0.00010773923,0.000008866164,0.00001639753],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99664915,0.00012508123,0.00065356056,0.000759473,0.0014671847,0.0003455381],"domain_scores_gemma":[0.99507713,0.00046415016,0.0005716619,0.0010967352,0.0026023425,0.00018798723],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0023247045,0.0001483053,0.00018208825,0.00025372783,0.00081012375,0.0011555251,0.006022357,0.0000581343,0.000035864563],"category_scores_gemma":[0.0050449027,0.00011890722,0.000056286786,0.0005908736,0.00039010347,0.0070902384,0.0013214772,0.00036922612,0.000031018462],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040939212,0.000056908717,0.9735933,0.00000326129,0.000027559754,0.0000024133262,0.0001540395,0.00022398273,0.000014544337,0.01069626,0.00332818,0.011858601],"study_design_scores_gemma":[0.0008513509,0.00028856978,0.90647036,0.00009403239,0.0000094500765,0.000047872578,0.000014597912,0.07478,0.000033205255,0.0054846606,0.011734413,0.00019146912],"about_ca_topic_score_codex":0.00029605083,"about_ca_topic_score_gemma":0.00025763252,"teacher_disagreement_score":0.43730855,"about_ca_system_score_codex":0.00013710506,"about_ca_system_score_gemma":0.00030050168,"threshold_uncertainty_score":0.9998814},"labels":[],"label_agreement":null},{"id":"W2891699219","doi":"10.23889/ijpds.v3i4.591","title":"Factors associated with screen-detected breast cancer across five Canadian provinces: a CanIMPACT study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Nova Scotia Health Authority; Manitoba Health; Queen's University; CancerCare Manitoba; BC Cancer Agency","funders":"","keywords":"Residence; Breast cancer; Medicine; Demography; Cancer; Breast cancer screening; Cancer registry; Mammography; Internal medicine","score_opus":0.19452608848111705,"score_gpt":0.459265154653927,"score_spread":0.26473906617280996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891699219","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993239,0.00001212399,0.00023318503,0.00072441273,0.00075777544,0.0004624477,0.004460072,0.000026722097,0.00008428807],"genre_scores_gemma":[0.99852574,0.000002334653,0.00017305164,0.00024867168,0.00053103844,0.00000777143,0.00039024532,0.0000129320315,0.000108197484],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974222,0.000025189012,0.0003196297,0.00041292544,0.0013502635,0.00046978344],"domain_scores_gemma":[0.9966212,0.000041724386,0.0002979433,0.00030693653,0.0022610158,0.00047117524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009506222,0.0001515235,0.0001766031,0.00027248997,0.000819111,0.00044124637,0.0011193157,0.000042509164,0.00013533638],"category_scores_gemma":[0.0008903453,0.00010533039,0.000035758945,0.0005924328,0.0002427005,0.001902565,0.00012679423,0.00018929885,0.000002945762],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002716316,0.000057729296,0.99393594,0.0000011534082,0.00013428484,0.00002254207,0.0007738743,0.000069012065,0.00013083084,0.000016232018,0.0006455199,0.0039412724],"study_design_scores_gemma":[0.0010994269,0.00047849084,0.9900921,0.00019696914,0.000051909945,0.00011049787,0.002383941,0.0051341,0.000044810615,0.00002036216,0.0002495285,0.00013788474],"about_ca_topic_score_codex":0.35762617,"about_ca_topic_score_gemma":0.76170975,"teacher_disagreement_score":0.40408358,"about_ca_system_score_codex":0.0016854898,"about_ca_system_score_gemma":0.0021222369,"threshold_uncertainty_score":0.64665145},"labels":[],"label_agreement":null},{"id":"W2891707081","doi":"10.23889/ijpds.v3i4.821","title":"Connecting the dots: a qualitative study of dog-bite data in Calgary (AB, Canada)","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Rabies epidemiology and control","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Mount Royal University","funders":"","keywords":"Business; Enforcement; Listing (finance); Incentive; Qualitative research; Medicine; Qualitative property; Public relations; Political science; Finance; Economics","score_opus":0.10460008740265923,"score_gpt":0.4479889349875899,"score_spread":0.34338884758493066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891707081","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99225825,0.00015456144,0.0019411845,0.0017151526,0.003113452,0.00024454674,0.0004903122,0.000004299127,0.00007822216],"genre_scores_gemma":[0.9989746,0.0000073408637,0.00021463982,0.00027947605,0.000119316515,0.0000041869994,0.00035238822,0.0000035160824,0.000044485045],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99837214,0.00037057433,0.0005549188,0.00032569555,0.00017575707,0.00020092502],"domain_scores_gemma":[0.99749494,0.0009952466,0.00044433342,0.0006254562,0.00042197973,0.000018046048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051433216,0.000077625526,0.00016078039,0.00013542794,0.00047668722,0.000033839413,0.0032147437,0.000040661696,0.000050111208],"category_scores_gemma":[0.0047506695,0.000053207812,0.000014360275,0.0001817418,0.00030195384,0.0006882089,0.0006157434,0.00023005292,0.0000030843107],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040873094,0.0018457362,0.6605616,0.000025103314,0.0023151666,0.000059113634,0.07819799,0.0013236296,0.048482336,0.055868458,0.047492232,0.09974129],"study_design_scores_gemma":[0.010914342,0.0012379136,0.7391192,0.00022453914,0.0001555438,0.00071690476,0.13083053,0.044857144,0.0008326638,0.007487842,0.06293815,0.0006852466],"about_ca_topic_score_codex":0.15858378,"about_ca_topic_score_gemma":0.4441613,"teacher_disagreement_score":0.2855775,"about_ca_system_score_codex":0.00009042419,"about_ca_system_score_gemma":0.00034015105,"threshold_uncertainty_score":0.8470193},"labels":[],"label_agreement":null},{"id":"W2891707856","doi":"10.23889/ijpds.v3i4.738","title":"Utilization of Radiotherapy for Bladder Cancer: Evolving referral and practice patterns in the general population","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Bladder and Urothelial Cancer Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University","funders":"","keywords":"Cystectomy; Medicine; Bladder cancer; Referral; Logistic regression; Population; Cancer registry; Radiation therapy; Cohort; Cancer; General surgery; Internal medicine; Emergency medicine; Family medicine; Environmental health","score_opus":0.15467151309004548,"score_gpt":0.4848082886634835,"score_spread":0.330136775573438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891707856","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.948803,0.00047641306,0.039588347,0.0074596745,0.0020254962,0.0009908555,0.00052703015,0.000011075743,0.00011808325],"genre_scores_gemma":[0.9870305,0.0002809935,0.010727236,0.0007120038,0.00086749723,0.000020778882,0.0003143964,0.000008391126,0.00003820992],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987847,0.0000379676,0.00030907453,0.00021840991,0.0005216359,0.00012821693],"domain_scores_gemma":[0.99874234,0.00012278267,0.0002470311,0.0001899409,0.0006566654,0.000041254003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010610173,0.00007339192,0.00010420979,0.00019196412,0.00017714758,0.00011359151,0.0003642247,0.000028707795,0.000030715826],"category_scores_gemma":[0.0006689474,0.000052009837,0.000026110753,0.00016854865,0.000078566416,0.001438073,0.00003688598,0.000059278027,1.4638337e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020615237,0.0002879609,0.8175677,0.000038049504,0.00019669926,0.0000038804897,0.0020231516,0.00019506023,0.00442997,0.0048249774,0.0018916803,0.16647935],"study_design_scores_gemma":[0.002195856,0.00033673082,0.9337633,0.00010190496,0.00007535546,0.00019733884,0.00021870107,0.05702089,0.00026546285,0.00066451414,0.0050787823,0.00008111948],"about_ca_topic_score_codex":0.001467474,"about_ca_topic_score_gemma":0.0003756245,"teacher_disagreement_score":0.16639823,"about_ca_system_score_codex":0.00015754307,"about_ca_system_score_gemma":0.00011907378,"threshold_uncertainty_score":0.22183914},"labels":[],"label_agreement":null},{"id":"W2891713478","doi":"10.23889/ijpds.v3i4.674","title":"Linking air pollution and administrative health databases to examine health effects of wildfire smoke exposure in Calgary, Canada in 2015","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Poisson regression; Medicine; Environmental health; Air pollution; Smoke; Air quality index; Logistic regression; Population; Population health; Demography; Meteorology; Geography","score_opus":0.11470212159888707,"score_gpt":0.43928580538110507,"score_spread":0.324583683782218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891713478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9703241,0.00009324483,0.004795346,0.023242524,0.00082283776,0.00043655522,0.00026000204,0.0000044018057,0.00002100172],"genre_scores_gemma":[0.98713475,0.000050182858,0.0069943625,0.0055639055,0.00009736431,0.0000036078263,0.00014020644,0.000004161287,0.000011452382],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99796075,0.00009951294,0.000558737,0.0003162267,0.0007548797,0.00030990053],"domain_scores_gemma":[0.99898785,0.000112648646,0.00035949206,0.00020418025,0.000039057522,0.00029675555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023747014,0.00008738349,0.00015931923,0.00018484629,0.00024785777,0.000033017608,0.00057231565,0.000018603152,0.00001287137],"category_scores_gemma":[0.00084866665,0.00008246665,0.00000784972,0.0003874498,0.00016695405,0.0012918559,0.00027661538,0.00012457678,8.4314536e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020679728,0.00016445259,0.8623979,0.00007883751,0.0000059835024,0.0000111575,0.0026408725,0.0010061791,0.00020579522,0.0010017467,0.009105872,0.12317439],"study_design_scores_gemma":[0.00044610933,0.0003661189,0.9892345,0.0003034139,7.90499e-7,0.00002299542,0.00012555206,0.005001408,0.00008098451,0.00018939642,0.0041509173,0.000077797544],"about_ca_topic_score_codex":0.5202905,"about_ca_topic_score_gemma":0.8372864,"teacher_disagreement_score":0.31699595,"about_ca_system_score_codex":0.0011050503,"about_ca_system_score_gemma":0.0010050912,"threshold_uncertainty_score":0.48290396},"labels":[],"label_agreement":null},{"id":"W2891732189","doi":"10.23889/ijpds.v3i4.1019","title":"Trends in Socioeconomic Inequalities in Hypertension in Ontario, Canada, 2000-2012","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Institute for Work & Health; University of Toronto; Public Health Ontario","funders":"","keywords":"Socioeconomic status; Inequality; Poisson regression; Medicine; Demography; Relative risk; Ethnic group; Confidence interval; Geography; Environmental health; Population; Mathematics; Political science; Sociology","score_opus":0.1172751557664263,"score_gpt":0.4040715148304295,"score_spread":0.28679635906400325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891732189","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98572046,0.00002989712,0.000027449978,0.009296851,0.0034352096,0.000082142134,0.00006238528,0.000004068629,0.0013415683],"genre_scores_gemma":[0.9967302,0.000021150807,0.00034521264,0.0012103268,0.00033809824,0.0000033987108,0.00007490475,0.0000036583888,0.0012730616],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99826384,0.00006188942,0.0004997152,0.00022769158,0.000563187,0.00038365947],"domain_scores_gemma":[0.99931645,0.00012925168,0.00014825207,0.00012810703,0.00016597357,0.00011194488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026799154,0.000066131215,0.00012744116,0.00059599924,0.00030186173,0.00017495068,0.0009968003,0.00004234296,0.00061742903],"category_scores_gemma":[0.00046175925,0.00006606364,0.000017927548,0.0002482593,0.00016560394,0.002426715,0.00011080782,0.00017307598,0.0000036095937],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027719234,0.00002257128,0.9762617,0.000001427168,0.000001606927,0.000008216474,0.0024449676,0.000087876615,0.000002531406,0.009621576,0.0034723154,0.008047541],"study_design_scores_gemma":[0.00036463098,0.000009164318,0.95245624,0.000041256128,7.183444e-7,0.000005092099,0.0012941315,0.0017085955,0.0000013689912,0.0015153429,0.042522736,0.00008074744],"about_ca_topic_score_codex":0.9944137,"about_ca_topic_score_gemma":0.99987566,"teacher_disagreement_score":0.03905042,"about_ca_system_score_codex":0.0036011003,"about_ca_system_score_gemma":0.0033730082,"threshold_uncertainty_score":0.94167525},"labels":[],"label_agreement":null},{"id":"W2891737049","doi":"10.23889/ijpds.v3i4.936","title":"The BC SUPPORT Unit Data Platform: Offering Data-Related Services To Researchers In British Columbia","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ministry of Health; Centre for Advancing Health Outcomes; Vancouver Coastal Health; University of British Columbia; Island Health; BC Children's Hospital; Provincial Health Services Authority","funders":"","keywords":"Electronic data capture; Data quality; Data management; Data collection; Data governance; Data management plan; Data access; Computer science; Transparency (behavior); Knowledge management; Process management; Data science; Business; Database; Service (business); Computer security","score_opus":0.3955946844684659,"score_gpt":0.5652210251444455,"score_spread":0.1696263406759796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891737049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94921535,0.00013357717,0.0009288955,0.024329146,0.013510167,0.0016193375,0.008031047,0.000079256315,0.002153244],"genre_scores_gemma":[0.9612183,0.00048016038,0.0055734823,0.008359137,0.002101064,0.000033260992,0.014952864,0.000042940224,0.007238792],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99634296,0.00012914628,0.0009540965,0.00060535426,0.0013040064,0.00066442444],"domain_scores_gemma":[0.99600065,0.00058159075,0.00037237708,0.0017810882,0.0009789114,0.00028537473],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.010895418,0.000082513754,0.00015671809,0.000214659,0.002919021,0.00094439054,0.010996963,0.00007747763,0.00051148614],"category_scores_gemma":[0.0025153672,0.00008728381,0.00001528038,0.0006300827,0.00019562876,0.0059728757,0.0059685097,0.00058446743,0.00011837441],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012001426,0.00003775816,0.7020168,0.000041379117,0.00003811005,0.000022436243,0.00061171333,0.000015408517,0.00005145633,0.00043602707,0.20667645,0.08993246],"study_design_scores_gemma":[0.000558272,0.000047222173,0.53237385,0.00015793237,0.0000062064496,0.00003408987,0.00087404787,0.012777772,4.7658628e-7,0.001147416,0.45191693,0.00010577501],"about_ca_topic_score_codex":0.06869744,"about_ca_topic_score_gemma":0.57935345,"teacher_disagreement_score":0.510656,"about_ca_system_score_codex":0.0005138606,"about_ca_system_score_gemma":0.0022096776,"threshold_uncertainty_score":0.99837905},"labels":[],"label_agreement":null},{"id":"W2891737726","doi":"10.23889/ijpds.v3i4.644","title":"Linking the Narcotics Monitoring System Database to Quantify the Contribution of Prescribed and Non-Prescribed Opioids to Opioid Overdoses in Ontario, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Ontario Drug Policy Research Network","funders":"","keywords":"Medical prescription; Medicine; Opioid; Pharmacy; Emergency medicine; Pharmacoepidemiology; Medical emergency; Family medicine; Internal medicine; Pharmacology","score_opus":0.044512285172492665,"score_gpt":0.3566729119450585,"score_spread":0.31216062677256584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891737726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98933446,0.000047753012,0.004782121,0.0022831042,0.0025562833,0.00073530414,0.00023763458,0.0000058371816,0.000017519866],"genre_scores_gemma":[0.99615043,0.000008946755,0.0031254576,0.00017583134,0.00029782794,0.000014638699,0.00019259824,0.0000071439163,0.00002710047],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980941,0.000027946207,0.00043698453,0.00027622047,0.0009481809,0.00021661384],"domain_scores_gemma":[0.9983141,0.00013678486,0.00017885803,0.00046414387,0.0007784232,0.00012772603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010140575,0.000104205465,0.00014714942,0.00017870625,0.00032345913,0.00016914608,0.00091425906,0.000021549782,0.0000051337493],"category_scores_gemma":[0.0008571283,0.000066426095,0.000020154668,0.00027577835,0.00008155738,0.00053714804,0.00043703892,0.0001484651,9.171553e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040505367,0.000066887966,0.98655003,0.000023287848,0.000055536537,0.000011518372,0.0016981284,0.0005389381,0.006462606,0.0015928973,0.00067308825,0.0019220372],"study_design_scores_gemma":[0.0008416276,0.00014457107,0.9795797,0.0007540281,0.000040886014,0.0000592896,0.0009266128,0.011206776,0.003265423,0.00004771076,0.003049083,0.000084325446],"about_ca_topic_score_codex":0.62037146,"about_ca_topic_score_gemma":0.67957866,"teacher_disagreement_score":0.059207242,"about_ca_system_score_codex":0.0009211149,"about_ca_system_score_gemma":0.0010333186,"threshold_uncertainty_score":0.38215655},"labels":[],"label_agreement":null},{"id":"W2891745186","doi":"10.23889/ijpds.v3i4.715","title":"The Canadian Urban Environmental Health Research Consortium (CANUE): a national data linkage initiative","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; University of Victoria; McGill University Health Centre","funders":"","keywords":"Data sharing; Environmental data; Biobank; Geospatial analysis; Metadata; Confidentiality; Data science; Environmental resource management; Environmental health; Business; Environmental planning; Geography; Computer science; Political science; Medicine; World Wide Web; Environmental science","score_opus":0.29790858237811446,"score_gpt":0.4758946121106599,"score_spread":0.17798602973254546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891745186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6469719,0.00078541966,0.029506847,0.20228404,0.023691643,0.0089413095,0.040348034,0.00019645771,0.04727434],"genre_scores_gemma":[0.99143237,0.00013437207,0.002945876,0.0028151956,0.0009854673,0.000016952577,0.0013844068,0.000018575294,0.00026676114],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9937135,0.00033413732,0.00061249104,0.0009863947,0.0034807194,0.0008727317],"domain_scores_gemma":[0.9971931,0.00053345825,0.0003898414,0.0010481338,0.00019808828,0.0006373733],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.01750191,0.00015232456,0.000115891846,0.0003121525,0.0058642267,0.00081557455,0.0056210523,0.000056965022,0.00058026786],"category_scores_gemma":[0.0036767945,0.000128082,0.000027096463,0.000453028,0.0024844734,0.003733494,0.0021378843,0.0005605025,0.00044239868],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022729531,0.0003757822,0.41578677,0.000008615908,0.00015413409,0.00004177257,0.003575743,0.00045112392,0.0015278319,0.009672127,0.34678307,0.22139572],"study_design_scores_gemma":[0.00048038128,0.00013024191,0.4180608,0.000035734334,0.000005094329,0.000099523975,0.00041416328,0.0459431,0.000058865535,0.003878559,0.5306768,0.00021677867],"about_ca_topic_score_codex":0.025342612,"about_ca_topic_score_gemma":0.15730217,"teacher_disagreement_score":0.3444605,"about_ca_system_score_codex":0.0039867903,"about_ca_system_score_gemma":0.0014095529,"threshold_uncertainty_score":0.99983674},"labels":[],"label_agreement":null},{"id":"W2891777309","doi":"10.23889/ijpds.v3i4.920","title":"Changes in Development Among Kindergarten Children in Ontario 2012-2015: Linking Developmental, Sociodemographic, and Policy Implementation Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University","funders":"","keywords":"Neighbourhood (mathematics); Socioeconomic status; Psychology; Developmental psychology; Early childhood; Child development; Vulnerability (computing); Cognitive development; Competence (human resources); Cognition; Demography; Population; Social psychology; Sociology","score_opus":0.08830970654641063,"score_gpt":0.43074696511591276,"score_spread":0.34243725856950213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891777309","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9913897,0.000028012888,0.00038848052,0.006239931,0.0011303441,0.0004111001,0.000047529447,0.000016973287,0.00034796298],"genre_scores_gemma":[0.98209,0.00010402783,0.01536122,0.0004961266,0.00056589337,0.000010841889,0.0011667095,0.000008427952,0.00019673488],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99753827,0.00006247706,0.0005063271,0.0005132469,0.0009808624,0.00039879195],"domain_scores_gemma":[0.99896306,0.000054650875,0.00028268658,0.00023146672,0.00030364175,0.00016446829],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003852471,0.00012107699,0.00011691827,0.0011074586,0.0009215045,0.0006283169,0.0019133837,0.000059444697,0.00015652346],"category_scores_gemma":[0.000328048,0.00012574533,0.000010827654,0.00060503057,0.00032753395,0.0041333046,0.00066169683,0.00018881966,0.000005979158],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007960254,0.000031552554,0.95652205,7.526506e-7,0.000014032146,6.3493206e-7,0.01404575,0.0000020709174,0.00001159146,0.0010794434,0.0006682753,0.027615892],"study_design_scores_gemma":[0.000501392,0.000011374064,0.97765845,0.000059349924,0.0000028194277,0.000009619266,0.0020154864,0.00008067326,0.00001672161,0.0011523113,0.018335626,0.00015619281],"about_ca_topic_score_codex":0.090737104,"about_ca_topic_score_gemma":0.9279967,"teacher_disagreement_score":0.8372596,"about_ca_system_score_codex":0.0012042882,"about_ca_system_score_gemma":0.00433486,"threshold_uncertainty_score":0.9153178},"labels":[],"label_agreement":null},{"id":"W2891842377","doi":"10.23889/ijpds.v3i4.1036","title":"Understanding the social determinants of opioid related hospitalizations","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Statistics Canada","funders":"","keywords":"Census; Demography; Intervention (counseling); Medicine; Cohort; Population; Environmental health; Gerontology; Geography; Psychiatry; Sociology","score_opus":0.14117123573647766,"score_gpt":0.43365431854524344,"score_spread":0.2924830828087658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891842377","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97109437,0.000032601332,0.02254591,0.0025238064,0.002746559,0.00035138326,0.0002100199,0.000018190323,0.00047713378],"genre_scores_gemma":[0.99800897,0.0000205166,0.0013633135,0.00008351174,0.00025763817,0.0000027976014,0.00016192152,0.0000070412743,0.000094268245],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99870574,0.000012823411,0.00033645288,0.00017116098,0.0006459046,0.0001279297],"domain_scores_gemma":[0.99884653,0.000040540086,0.00027222483,0.00022424202,0.0005702912,0.000046173947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054280175,0.00006200549,0.00009054852,0.00018361672,0.00060394977,0.000093460214,0.00069180486,0.000025633335,0.000052917396],"category_scores_gemma":[0.00047287275,0.000042754757,0.000042442927,0.000296258,0.00033741607,0.0007091283,0.00014175187,0.000061261424,0.000004577247],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026550857,0.00040576668,0.91319156,0.00002536785,0.00023390037,0.000010978956,0.0062407493,0.000064928,0.0017322942,0.062115103,0.004597525,0.011116333],"study_design_scores_gemma":[0.0017132332,0.0002911514,0.9300386,0.00015924971,0.00012818958,0.00022540941,0.0017544247,0.046049614,0.0006307538,0.01737965,0.0014975672,0.00013219581],"about_ca_topic_score_codex":0.000041271232,"about_ca_topic_score_gemma":0.000025564268,"teacher_disagreement_score":0.045984685,"about_ca_system_score_codex":0.00022812471,"about_ca_system_score_gemma":0.00022628403,"threshold_uncertainty_score":0.46451542},"labels":[],"label_agreement":null},{"id":"W2891872726","doi":"10.23889/ijpds.v3i4.742","title":"Facilitating Patient Recruitment Process for Research","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; University of Calgary; Alberta Health Services","funders":"","keywords":"Medicine; Family medicine; Formulary; Pharmacy; Health care; Patient recruitment; Medical emergency; Randomized controlled trial; Surgery","score_opus":0.8721069331731655,"score_gpt":0.7235606479454996,"score_spread":0.1485462852276659,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891872726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8867221,0.000023418888,0.090171106,0.0146553675,0.0047889086,0.0027002543,0.00063838094,0.000032784952,0.00026770885],"genre_scores_gemma":[0.9475408,0.000008658812,0.04954254,0.0006530611,0.0013754336,0.00008218947,0.0006927111,0.000010089826,0.00009451369],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967711,0.00004660567,0.0008360627,0.00040387307,0.0016532167,0.0002891231],"domain_scores_gemma":[0.99172395,0.0011303753,0.00035621697,0.00033712265,0.006288572,0.00016376327],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.007397979,0.000072571806,0.00010449841,0.00034860056,0.00065072405,0.00022989199,0.0007647888,0.000029610026,0.000080157966],"category_scores_gemma":[0.038469777,0.000061384766,0.00004213,0.000328929,0.00022752219,0.0018974304,0.0002166508,0.00017379904,0.000016189731],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022511906,0.0004190127,0.021120107,0.00005001391,0.00010678738,0.0000065258323,0.0017601821,0.00017727897,0.008166971,0.0035052632,0.021849696,0.940587],"study_design_scores_gemma":[0.00835473,0.005696939,0.044194996,0.00058625365,0.00014340284,0.0006689513,0.011609631,0.38339716,0.006454614,0.038782988,0.499588,0.0005223388],"about_ca_topic_score_codex":0.000073385825,"about_ca_topic_score_gemma":0.000053367643,"teacher_disagreement_score":0.9400646,"about_ca_system_score_codex":0.00033354023,"about_ca_system_score_gemma":0.00053738395,"threshold_uncertainty_score":0.9696296},"labels":[],"label_agreement":null},{"id":"W2891884985","doi":"10.23889/ijpds.v3i4.805","title":"Using Administrative Health Data to Define a Cohort of Youth Affected by Chronic Health Conditions: Preparing for Cross-Sectoral Data Linkage","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Alberta; University of Calgary","funders":"","keywords":"Medicine; Cohort; Health care; Family medicine; Demography; Pediatrics","score_opus":0.49301812846068516,"score_gpt":0.532371241901925,"score_spread":0.03935311344123982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891884985","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18031602,0.0006474482,0.57257414,0.007598293,0.003899099,0.0023215178,0.23248537,0.000037866736,0.000120234225],"genre_scores_gemma":[0.95856935,0.000079695266,0.02227689,0.0008220437,0.0006190719,0.000010649256,0.017573033,0.0000141513765,0.00003512436],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974364,0.000029381277,0.001138994,0.00078573136,0.00022376835,0.0003857113],"domain_scores_gemma":[0.9968835,0.00006979384,0.0012353507,0.0012678945,0.00031294118,0.00023048102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005209765,0.00011797885,0.00029138706,0.00037752927,0.0006100821,0.0003488655,0.0033266626,0.000033705288,0.000025906556],"category_scores_gemma":[0.0016290334,0.00013252816,0.00002829834,0.00033413988,0.00015496425,0.0026675395,0.0011225499,0.00010019855,0.0000061191404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008951509,0.001658445,0.3602391,0.0011130726,0.0011888235,0.0000031425288,0.0043799197,0.0035487162,0.0007478098,0.4178154,0.17287834,0.03553209],"study_design_scores_gemma":[0.0026929772,0.001604315,0.22573417,0.0005527089,0.00002684807,0.0000438956,0.00022219575,0.63637847,0.0000974659,0.006663969,0.12534642,0.0006365851],"about_ca_topic_score_codex":0.007875156,"about_ca_topic_score_gemma":0.0027083647,"teacher_disagreement_score":0.7782533,"about_ca_system_score_codex":0.00065930566,"about_ca_system_score_gemma":0.0008046541,"threshold_uncertainty_score":0.9987315},"labels":[],"label_agreement":null},{"id":"W2891886419","doi":"10.23889/ijpds.v3i4.980","title":"In-Utero SSRI and SNRI Exposure and the Risk of Long Term Adverse Mental and Educational Outcomes in Children: A Population-Based Retrospective Cohort Study Utilizing Linked Administrative Data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal Mental Health During Pregnancy and Postpartum","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Mood; Medicine; Hazard ratio; Population; Proportional hazards model; Anxiety; Pregnancy; Cohort; Cohort study; Propensity score matching; Confounding; Retrospective cohort study; Mental health; Pediatrics; Psychiatry; Psychology; Internal medicine; Environmental health; Confidence interval","score_opus":0.04977355950166561,"score_gpt":0.41675894419983217,"score_spread":0.36698538469816655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891886419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99661714,0.000088094705,0.000038089172,0.0011209267,0.00052453217,0.0010441919,0.00055380317,0.0000030950239,0.000010136111],"genre_scores_gemma":[0.9985578,0.000079239115,0.0006966506,0.000118624615,0.00013008485,0.000014024249,0.0003780677,0.0000053353865,0.000020189877],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983381,0.00008501928,0.000506369,0.00038845235,0.0005457661,0.00013628583],"domain_scores_gemma":[0.9988904,0.00017735279,0.00037173802,0.00032076187,0.00015705878,0.00008270738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017811991,0.000107335014,0.00021621164,0.00024196593,0.00024340946,0.000072472496,0.00042756007,0.000027862134,0.000017246803],"category_scores_gemma":[0.00063525455,0.00007669061,0.000014708127,0.00012847781,0.0003071238,0.001115634,0.00027447726,0.00017141979,2.4920183e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055912236,0.00015445946,0.99807805,0.00002028554,0.000045623685,0.000003285986,0.00045507317,0.0000016959061,0.000005736167,0.0002567237,0.0000031083543,0.00041681444],"study_design_scores_gemma":[0.003421513,0.0002232612,0.99197596,0.00039582065,0.000040618757,0.00015020902,0.00014593205,0.0032214792,0.0000134416,0.00034320573,0.0000012378838,0.00006729609],"about_ca_topic_score_codex":0.001178235,"about_ca_topic_score_gemma":0.0010479493,"teacher_disagreement_score":0.0061020865,"about_ca_system_score_codex":0.00012120031,"about_ca_system_score_gemma":0.00012719297,"threshold_uncertainty_score":0.31273523},"labels":[],"label_agreement":null},{"id":"W2891886878","doi":"10.23889/ijpds.v3i4.760","title":"Learning Unsupervised Representations from Biomedical Text","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Institute for Clinical Evaluative Sciences; University of Toronto","funders":"","keywords":"Computer science; Topic model; Natural language processing; Word2vec; Information retrieval; Statistical model; Artificial intelligence; Data science; Embedding","score_opus":0.13435178578016807,"score_gpt":0.511399824377993,"score_spread":0.377048038597825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891886878","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46004617,0.00005562044,0.50431293,0.01716383,0.011236142,0.00030347152,0.00032515396,0.00013496826,0.0064217146],"genre_scores_gemma":[0.94315773,0.000029872897,0.051591758,0.0001996247,0.003631551,0.0000032783976,0.0006219808,0.000006149135,0.00075806037],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99724084,0.0001697019,0.0003770687,0.0003785738,0.0016044915,0.00022932825],"domain_scores_gemma":[0.9974769,0.000524929,0.00023531739,0.00022130553,0.0013340195,0.00020755654],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0030997174,0.000072741335,0.000098404926,0.00038821783,0.002017635,0.00071249256,0.0019911057,0.000040436138,0.0008466593],"category_scores_gemma":[0.0053937486,0.000067584755,0.000061957384,0.0007359479,0.0007172925,0.0021608283,0.00026987825,0.0001420376,0.000053946267],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015193033,0.00026208468,0.1389899,0.0000020244586,0.00024287707,0.000013108044,0.010627724,0.0010226159,0.003657668,0.10754763,0.011536282,0.7259461],"study_design_scores_gemma":[0.00085022475,0.00009516009,0.19356753,0.000044538774,0.000059174658,0.000014922921,0.0033302207,0.1832568,0.000084061685,0.07878734,0.53960395,0.00030605582],"about_ca_topic_score_codex":0.0032899743,"about_ca_topic_score_gemma":0.0007974424,"teacher_disagreement_score":0.7256401,"about_ca_system_score_codex":0.00015367284,"about_ca_system_score_gemma":0.00041386354,"threshold_uncertainty_score":0.9992816},"labels":[],"label_agreement":null},{"id":"W2891896859","doi":"10.23889/ijpds.v3i4.1031","title":"Measuring the impact of transition on children aging out of child protective services","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child Abuse and Trauma","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Medical prescription; Medicine; Population; Foster care; Transitional care; Community service; Health care; Psychiatry; Family medicine; Environmental health; Nursing; Political science","score_opus":0.07407631324300926,"score_gpt":0.4063248217931432,"score_spread":0.332248508550134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891896859","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99266624,0.000022805745,0.0041157953,0.00068127457,0.0011441729,0.00027625318,0.00038616898,0.000008062315,0.0006992034],"genre_scores_gemma":[0.9990883,0.0000024534704,0.0001222445,0.000071599425,0.0006286114,0.000002528253,0.00007273166,0.000005666918,0.0000058560754],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9988478,0.000035254554,0.0002865498,0.00020343575,0.00050396804,0.00012301236],"domain_scores_gemma":[0.99884003,0.000042061085,0.0003464306,0.00030083247,0.00043637108,0.000034264038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007971082,0.00007205943,0.00008605326,0.00021954707,0.0002594435,0.00006620077,0.0011702264,0.000021899052,0.00009123196],"category_scores_gemma":[0.00005964359,0.000046842673,0.000072542825,0.00016067625,0.00015486171,0.00074499345,0.000059943384,0.00011683726,0.0000063487582],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005719593,0.0030294247,0.3850036,0.000054247994,0.0042994833,0.000011706957,0.100433566,0.020666327,0.018302474,0.048931416,0.002952967,0.4105952],"study_design_scores_gemma":[0.00061083795,0.00021251131,0.9933671,0.00016161473,0.00001618837,0.000069249836,0.00013930057,0.0023246047,0.0016922757,0.001304946,0.00003756222,0.00006383379],"about_ca_topic_score_codex":0.00070523325,"about_ca_topic_score_gemma":0.00009112274,"teacher_disagreement_score":0.6083635,"about_ca_system_score_codex":0.000053485957,"about_ca_system_score_gemma":0.000035129335,"threshold_uncertainty_score":0.21745911},"labels":[],"label_agreement":null},{"id":"W2891907080","doi":"10.23889/ijpds.v3i4.667","title":"Life expectancy and health-adjusted life expectancy are decreased in people living with inflammatory bowel disease: a population-based matched cohort study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bruyère; University of Ottawa; Institute for Clinical Evaluative Sciences; Ottawa Hospital; Children's Hospital of Eastern Ontario","funders":"","keywords":"Life expectancy; Medicine; Inflammatory bowel disease; Demography; Cohort; Population; Cohort study; Gerontology; Disease; Internal medicine; Environmental health","score_opus":0.07686992005683431,"score_gpt":0.4496728668074105,"score_spread":0.3728029467505762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891907080","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98882896,0.0002723308,0.001559969,0.004540968,0.0020623386,0.0023729943,0.00024155837,0.00009444294,0.000026425172],"genre_scores_gemma":[0.9947588,0.000028541072,0.0017794907,0.0020198422,0.0008485986,0.00019201144,0.00030170902,0.000036596404,0.000034416124],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99465925,0.00043980684,0.0014615122,0.00085681776,0.0018518005,0.0007308383],"domain_scores_gemma":[0.99445105,0.00054724846,0.001410792,0.0007480773,0.0015318795,0.0013109342],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0038329253,0.00027459805,0.00042875335,0.0007633764,0.0017769885,0.00019974425,0.0012784852,0.000083710875,0.00015396766],"category_scores_gemma":[0.007060612,0.00024527137,0.000038509665,0.00070420804,0.0001296917,0.0020349487,0.0003633342,0.00042390006,0.000019772246],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033856338,0.00017986912,0.9962107,0.00008228901,0.000022740154,0.000009087856,0.0016419885,0.00014086028,0.0000030928893,0.00023144594,0.0010290282,0.00011035726],"study_design_scores_gemma":[0.00184706,0.00015512973,0.9743405,0.0012896768,0.000019794272,0.0000058112378,0.005340647,0.016518546,2.7077283e-7,0.0001215803,0.00012239935,0.00023858678],"about_ca_topic_score_codex":0.0049423724,"about_ca_topic_score_gemma":0.02584951,"teacher_disagreement_score":0.021870181,"about_ca_system_score_codex":0.0012392608,"about_ca_system_score_gemma":0.003573172,"threshold_uncertainty_score":0.99999994},"labels":[],"label_agreement":null},{"id":"W2891918393","doi":"10.23889/ijpds.v3i4.726","title":"ICD coding training worldwide","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Certification; Coding (social sciences); Descriptive statistics; Benchmarking; Medical classification; Medical education; Business; Psychology; Medicine; Marketing; Political science; Nursing; Statistics","score_opus":0.5815781486454729,"score_gpt":0.5942205993081467,"score_spread":0.012642450662673888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891918393","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23637064,0.000047036654,0.61555356,0.027839005,0.072272755,0.0014091963,0.0005848368,0.00029335136,0.045629587],"genre_scores_gemma":[0.9758744,0.00002473978,0.015293253,0.0033582451,0.0043534758,0.000011507831,0.00025767816,0.000008221086,0.00081846747],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975544,0.000063594875,0.0007581102,0.00022285391,0.0009831059,0.00041793264],"domain_scores_gemma":[0.99745494,0.00033673208,0.0005215183,0.00027719777,0.0011586421,0.00025098474],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0058793235,0.00007565486,0.000110702684,0.00036997366,0.002580656,0.000120381155,0.0014159299,0.00005640506,0.0008120022],"category_scores_gemma":[0.0048622806,0.00006353236,0.000024363615,0.00028414204,0.00016871702,0.0024383229,0.00026449916,0.00037431295,0.00015527998],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005174523,0.000069579495,0.12259487,0.00012600921,0.00006366229,0.0000072523303,0.014922367,0.00012232162,0.0011798841,0.15593731,0.22802034,0.47643897],"study_design_scores_gemma":[0.0015999223,0.00012196699,0.10806029,0.00070102466,0.000015427831,0.00005593929,0.0022473675,0.2430147,0.000028773105,0.009527195,0.6343793,0.00024807412],"about_ca_topic_score_codex":0.00009429799,"about_ca_topic_score_gemma":0.00009375137,"teacher_disagreement_score":0.73950374,"about_ca_system_score_codex":0.00029266547,"about_ca_system_score_gemma":0.00069535495,"threshold_uncertainty_score":0.99871784},"labels":[],"label_agreement":null},{"id":"W2891923978","doi":"10.23889/ijpds.v3i4.971","title":"Measuring Trends in Health Inequalities across Urban Cities in Canada: A Focus on Health System Outcomes","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Saskatchewan Health Authority; University of Saskatchewan; Canadian Institute for Health Information","funders":"","keywords":"Inequality; Census; Geography; Metropolitan area; Demography; Health care; Neighbourhood (mathematics); Medicine; Socioeconomics; Environmental health; Economic growth; Population; Economics; Sociology","score_opus":0.20349394003908633,"score_gpt":0.464971008935538,"score_spread":0.26147706889645167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891923978","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83578044,0.00026772326,0.0006674896,0.1473272,0.012591606,0.000538844,0.0014915918,0.000054133754,0.0012809508],"genre_scores_gemma":[0.9962257,0.00005203891,0.00032282693,0.002560315,0.00054704084,0.000009115366,0.000048950373,0.000007805015,0.00022620996],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99603367,0.00022485945,0.0009563663,0.00033487787,0.0016461833,0.0008040538],"domain_scores_gemma":[0.9984306,0.00025791107,0.000489851,0.00024520597,0.00027755485,0.0002988682],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007110487,0.000118050906,0.00028621536,0.0005366735,0.0012570154,0.000373796,0.0014818065,0.000030260488,0.000023835844],"category_scores_gemma":[0.0010687667,0.00010771215,0.00003486087,0.00057174196,0.0001914828,0.0014444572,0.00015153205,0.00018829765,0.0000018206293],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043010466,0.000025503623,0.85226077,0.00003818396,0.000007003829,0.0000050249073,0.009166928,0.00014546918,1.4302694e-7,0.101111256,0.0026151491,0.034581535],"study_design_scores_gemma":[0.0005770741,0.000049822695,0.9612986,0.00045227216,5.8685634e-7,0.0000061016217,0.021028142,0.002055543,0.0000014125308,0.0007399324,0.013650671,0.00013987745],"about_ca_topic_score_codex":0.9798912,"about_ca_topic_score_gemma":0.9955069,"teacher_disagreement_score":0.16044523,"about_ca_system_score_codex":0.007368894,"about_ca_system_score_gemma":0.0052615283,"threshold_uncertainty_score":0.99644166},"labels":[],"label_agreement":null},{"id":"W2891961677","doi":"10.23889/ijpds.v3i3.431","title":"A Pan-Canadian Data Resource for Monitoring Child Developmental Health: The Canadian Neighbourhoods Early Child Development (CanNECD) Database","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Saskatchewan; Saskatchewan Health; Saskatchewan Health Authority; Manitoba Health; Learning Partnership; University of Manitoba; University of British Columbia; McMaster University","funders":"","keywords":"Socioeconomic status; Geography; Database; Population; Census; Neighbourhood (mathematics); Record linkage; Context (archaeology); Environmental health; Medicine; Computer science","score_opus":0.14051414080863403,"score_gpt":0.4312693904114818,"score_spread":0.2907552496028478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891961677","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13128461,0.001076592,0.012776256,0.76542366,0.03860545,0.006305104,0.024111804,0.00017898064,0.020237561],"genre_scores_gemma":[0.96892893,0.00006312638,0.01947422,0.0058410256,0.003655112,0.000022788703,0.0017603444,0.000018482942,0.00023593931],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965483,0.00007933912,0.0005865202,0.0005368437,0.0012313682,0.0010176257],"domain_scores_gemma":[0.99728596,0.00016416855,0.00029364647,0.00056670146,0.0005810272,0.0011084831],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.006629932,0.00014369524,0.00014025289,0.00043769818,0.0127822785,0.0015881095,0.005632964,0.00005925976,0.00007245702],"category_scores_gemma":[0.0022640661,0.00012131106,0.00003065843,0.00041009785,0.00036386913,0.0029881636,0.0004620636,0.00024711352,0.000018103761],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001331205,0.00009589705,0.43215185,0.000056021698,0.00018896295,0.000013513961,0.021232411,0.000033975244,0.0000029429152,0.09346477,0.0874023,0.36522424],"study_design_scores_gemma":[0.00020661738,0.000014507954,0.28837678,0.00014546288,0.000003973888,0.000021038288,0.0013105829,0.0005256901,0.0000046673126,0.00014202051,0.7091158,0.00013283812],"about_ca_topic_score_codex":0.8700641,"about_ca_topic_score_gemma":0.9868929,"teacher_disagreement_score":0.83764434,"about_ca_system_score_codex":0.0023408132,"about_ca_system_score_gemma":0.010635566,"threshold_uncertainty_score":0.99974704},"labels":[],"label_agreement":null},{"id":"W2891964161","doi":"10.23889/ijpds.v3i4.710","title":"Internal and External Data Linkage of Complex Relational Database: Results from CorHealth Ontario","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Relational database; Database; Computer science; Record linkage; Linkage (software); Referral; Data mining; Cohort; Medicine; Population; Family medicine; Internal medicine","score_opus":0.2834305550450701,"score_gpt":0.46123493804697996,"score_spread":0.17780438300190987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891964161","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86367464,0.00017822736,0.098569624,0.0042760656,0.0051591867,0.00072875986,0.022888932,0.000048907576,0.004475638],"genre_scores_gemma":[0.92894757,0.000057021796,0.052260403,0.00027914485,0.001267259,0.000001301177,0.016590463,0.000010373242,0.00058644125],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970468,0.000025441197,0.00076431443,0.0006316531,0.0013226485,0.000209089],"domain_scores_gemma":[0.9972947,0.00016779493,0.0005988979,0.0010586109,0.00067144184,0.00020852812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015445547,0.00012757926,0.00018734534,0.00030379093,0.00025093052,0.0002497191,0.001923154,0.000032173757,0.00043426434],"category_scores_gemma":[0.0011151602,0.00011517299,0.000029259458,0.00015246747,0.0004941057,0.003151809,0.0015166433,0.00019847014,0.00000872352],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011507996,0.0011773598,0.6940305,0.00015552617,0.0010756222,0.00018415725,0.001990803,0.00021862827,0.012997211,0.051853072,0.11826902,0.10654008],"study_design_scores_gemma":[0.0035345228,0.0001678783,0.8722778,0.0004514291,0.00010489187,0.00013526116,0.0001036128,0.084643245,0.000045347857,0.0020323705,0.03636612,0.00013753184],"about_ca_topic_score_codex":0.024573047,"about_ca_topic_score_gemma":0.011013487,"teacher_disagreement_score":0.17824726,"about_ca_system_score_codex":0.00029829747,"about_ca_system_score_gemma":0.0008417436,"threshold_uncertainty_score":0.9819224},"labels":[],"label_agreement":null},{"id":"W2891964950","doi":"10.23889/ijpds.v3i4.879","title":"Can mental health related hospital visits be relied upon for suicide prevention?","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Suicide and Self-Harm Studies","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Saskatchewan Health Authority; University of Saskatchewan","funders":"","keywords":"Coroner; Medicine; Mental health; Suicide prevention; Psychiatry; Suicide methods; Norwegian; Poison control; Disadvantaged; Family medicine; Medical emergency","score_opus":0.09359138561534623,"score_gpt":0.45778676108302,"score_spread":0.3641953754676738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891964950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9229334,0.00026821927,0.007640623,0.044283375,0.021041991,0.0012198474,0.0018975138,0.000082572114,0.00063245115],"genre_scores_gemma":[0.9916346,0.000030147274,0.004244866,0.0007342689,0.00078862876,0.000024926829,0.0013288528,0.000016773683,0.0011969524],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9978168,0.000045718178,0.00062984735,0.00048468437,0.0006501118,0.00037280822],"domain_scores_gemma":[0.9982266,0.00009301921,0.0005308036,0.00034464133,0.0006663322,0.0001385977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017578884,0.00012879237,0.00016200294,0.00030168693,0.0010112801,0.00020381784,0.0013009579,0.000044756864,0.00020503634],"category_scores_gemma":[0.00050514896,0.00011826448,0.00007827544,0.00024485055,0.00012842726,0.0010279132,0.00022299311,0.00011857437,0.000021582051],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002558122,0.0016295211,0.2144128,0.000030505058,0.0015963095,0.000025012601,0.021053836,0.0001028082,0.0019341421,0.17399162,0.4613282,0.12133712],"study_design_scores_gemma":[0.010247679,0.004133013,0.826805,0.00016722849,0.00011299688,0.00066003087,0.005087742,0.013972818,0.00038640495,0.045960065,0.09134879,0.0011182235],"about_ca_topic_score_codex":0.0005496135,"about_ca_topic_score_gemma":0.00068376877,"teacher_disagreement_score":0.61239225,"about_ca_system_score_codex":0.00026445292,"about_ca_system_score_gemma":0.00017890698,"threshold_uncertainty_score":0.7778051},"labels":[],"label_agreement":null},{"id":"W2891985605","doi":"10.23889/ijpds.v3i4.756","title":"Health Equity in Cancer Screening in Calgary – A Geographic Approach to Account for Population Socioeconomic Status","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Women's College Hospital; University of Manitoba; Mount Sinai Hospital; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Socioeconomic status; Breast cancer screening; Social deprivation; Demography; Breast cancer; Medicine; Cancer screening; Health equity; Social class; Population; Environmental health; Gerontology; Cancer; Public health; Mammography; Sociology; Pathology","score_opus":0.23139745614676335,"score_gpt":0.5085167327155664,"score_spread":0.2771192765688031,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891985605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.927991,0.00017685832,0.06578832,0.0031975273,0.0013441588,0.0009847474,0.00036138354,0.000017386226,0.0001386177],"genre_scores_gemma":[0.95579606,0.000055109504,0.041065287,0.0017672955,0.00061501714,0.000052570762,0.0006191765,0.0000109345265,0.000018552893],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976255,0.000023060447,0.0006476263,0.00049140083,0.0007123297,0.00050007313],"domain_scores_gemma":[0.9987069,0.00004499773,0.0003100277,0.00025116597,0.00045307647,0.00023383707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026834765,0.000117866926,0.00023471657,0.0008186334,0.00028096722,0.00020614073,0.0007734826,0.000047342975,0.000018176725],"category_scores_gemma":[0.00044650811,0.00011433763,0.00005352076,0.0004067481,0.00008478518,0.0018357886,0.00027010095,0.0001739958,0.0000019547583],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004973707,0.000059530365,0.89620787,0.000017186216,0.000014927852,0.0000011462813,0.00021284983,0.0019386759,0.000084607884,0.0015388308,0.0005173636,0.09890966],"study_design_scores_gemma":[0.0011652117,0.00014620367,0.88531446,0.00022557241,0.0000070098818,0.000032307416,0.00012649932,0.11008668,0.000007857497,0.0010408937,0.0017361052,0.000111198264],"about_ca_topic_score_codex":0.022173276,"about_ca_topic_score_gemma":0.010326698,"teacher_disagreement_score":0.108148,"about_ca_system_score_codex":0.0011752323,"about_ca_system_score_gemma":0.0006103582,"threshold_uncertainty_score":0.98433816},"labels":[],"label_agreement":null},{"id":"W2891989525","doi":"10.23889/ijpds.v3i4.791","title":"Comparison of Health Behaviour Mortality Hazards in Canada and the United States","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada; Institute for Clinical Evaluative Sciences; Ottawa Hospital; Bruyère; University of Ottawa","funders":"","keywords":"National Health Interview Survey; Medicine; Environmental health; Hazard ratio; Demography; Proportional hazards model; Population; Community health; Hazard; Public health; Gerontology; Confidence interval","score_opus":0.3734426348304698,"score_gpt":0.5861470312120107,"score_spread":0.21270439638154093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891989525","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9879858,0.00005288053,0.00096928334,0.00734406,0.0025279426,0.00039554606,0.0006859256,0.0000050565354,0.00003352099],"genre_scores_gemma":[0.9975574,0.00006485854,0.0006345567,0.0010186168,0.00015973265,0.0000075781536,0.0005406891,0.000003843968,0.000012738856],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99755126,0.00026514722,0.0010038434,0.00018650854,0.0007289092,0.0002643348],"domain_scores_gemma":[0.9976938,0.00034163127,0.00078785577,0.0002667365,0.00080700626,0.00010300464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004641651,0.00006579211,0.0001982539,0.00024613453,0.001261263,0.00003280997,0.0009003596,0.000027333681,0.00004539233],"category_scores_gemma":[0.0009361392,0.000048795402,0.000014043876,0.00036170954,0.0003371689,0.0005511721,0.00028691476,0.00028791386,0.0000011795469],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006809678,0.000020451804,0.9845882,0.000015102881,0.000007638808,2.2331564e-7,0.0021811873,0.00025136568,8.5671996e-7,0.01006993,0.0017922462,0.0010046905],"study_design_scores_gemma":[0.0009112122,0.000030794734,0.8860369,0.00009654647,0.0000058476385,0.0000021097874,0.0040294067,0.10358504,0.000001649225,0.002519055,0.0027346762,0.000046783407],"about_ca_topic_score_codex":0.9495129,"about_ca_topic_score_gemma":0.95973676,"teacher_disagreement_score":0.103333674,"about_ca_system_score_codex":0.0005821914,"about_ca_system_score_gemma":0.0027145296,"threshold_uncertainty_score":0.9700743},"labels":[],"label_agreement":null},{"id":"W2891994155","doi":"10.23889/ijpds.v3i4.987","title":"Empathic Cultural Mapping: Little data, big data, knowledge transfer and exchange","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Government (linguistics); Public relations; Empowerment; Psychosocial; Sociology; Big data; Data science; Political science; Psychology; Computer science","score_opus":0.2582180060156925,"score_gpt":0.4432382665093945,"score_spread":0.18502026049370202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891994155","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8398412,0.0025785556,0.07701817,0.0072271745,0.019076468,0.0013070825,0.05098098,0.00021024392,0.0017601486],"genre_scores_gemma":[0.96951044,0.00026153534,0.0054872287,0.0003809892,0.0038614809,0.0000038041446,0.020068051,0.00001713843,0.0004093086],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99756676,0.000043499334,0.00044435466,0.000795683,0.000867225,0.00028248696],"domain_scores_gemma":[0.99685776,0.00007521862,0.0001292817,0.0016954928,0.00094847794,0.0002937675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022191233,0.00014570753,0.0001903742,0.0003039681,0.0003830365,0.0004234707,0.0035923976,0.00004424071,0.000109318076],"category_scores_gemma":[0.001637344,0.00011863153,0.000025593805,0.00033941932,0.00046770586,0.004207355,0.0016955831,0.00017510896,0.000050602048],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070769346,0.00052858103,0.15066779,0.0001634367,0.00031647872,0.00007095573,0.0017206501,0.0000033261558,0.006253277,0.001485212,0.1470491,0.6910335],"study_design_scores_gemma":[0.001763224,0.00011622203,0.33740646,0.00025234808,0.00006838004,0.00061714166,0.00019274384,0.07034337,0.00006807436,0.0002822388,0.5886291,0.0002606831],"about_ca_topic_score_codex":0.000106807005,"about_ca_topic_score_gemma":0.0003277585,"teacher_disagreement_score":0.69077283,"about_ca_system_score_codex":0.00009809204,"about_ca_system_score_gemma":0.00032533114,"threshold_uncertainty_score":0.66756284},"labels":[],"label_agreement":null},{"id":"W2892005286","doi":"10.23889/ijpds.v3i4.840","title":"Machine learning: how much does it improve the prediction of unplanned hospital admissions?","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Logistic regression; Machine learning; Decision tree; Random forest; Predictive modelling; Primary care; Medical record; Artificial intelligence; Lasso (programming language); Medicine; Computer science; Family medicine","score_opus":0.04399816139798792,"score_gpt":0.36658468993762877,"score_spread":0.32258652853964087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892005286","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17477705,0.00010988694,0.6230669,0.17079675,0.028856747,0.00092380197,0.00091705576,0.00020817318,0.00034365433],"genre_scores_gemma":[0.98156524,0.000028996043,0.016766572,0.00025065796,0.0008694121,0.00000564782,0.00013529531,0.000007717309,0.0003704369],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974971,0.000100751175,0.00041897566,0.00046000708,0.001264919,0.00025825467],"domain_scores_gemma":[0.9969034,0.00021643279,0.0006406352,0.0006957451,0.0013645972,0.00017914266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021075767,0.00011769147,0.00011307414,0.0002746064,0.00092105987,0.0006394135,0.0050259065,0.00004436226,0.0000369532],"category_scores_gemma":[0.0049583153,0.00007114399,0.00005178668,0.00042869168,0.00020494481,0.0031183357,0.0009247931,0.00034587568,0.0000042884585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026840979,0.0003900174,0.5725239,0.00006247416,0.00018452173,0.00001698697,0.006110995,0.0016858212,0.009502719,0.12910004,0.013912267,0.26624185],"study_design_scores_gemma":[0.00039666463,0.00044386348,0.04854549,0.00006259558,0.000007637039,0.00007709715,0.00016509072,0.89780676,0.000741211,0.0049595903,0.04667159,0.00012241669],"about_ca_topic_score_codex":0.00020948832,"about_ca_topic_score_gemma":0.00006078877,"teacher_disagreement_score":0.8961209,"about_ca_system_score_codex":0.00012154872,"about_ca_system_score_gemma":0.00030195204,"threshold_uncertainty_score":0.9339468},"labels":[],"label_agreement":null},{"id":"W2892008580","doi":"10.23889/ijpds.v3i4.947","title":"Meeting the challenge of data linkage for special populations","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Linkage (software); Record linkage; Population; Christian ministry; Medical record; Identifier; Unique identifier; Medicine; Data set; Demography; Computer science; Statistics; Biology; Environmental health; Genetics; Surgery; Mathematics; Political science; Law","score_opus":0.6449232329171355,"score_gpt":0.5775271401239062,"score_spread":0.06739609279322933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892008580","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016464533,0.00009113625,0.8920241,0.044141978,0.026244864,0.0013490496,0.013782689,0.000035912577,0.005865751],"genre_scores_gemma":[0.9260364,0.000034676577,0.061757237,0.0004965177,0.009182427,0.000009221651,0.0019085417,0.000011427532,0.0005635387],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9953919,0.00008908627,0.0010874572,0.0006441752,0.002553699,0.00023365265],"domain_scores_gemma":[0.99396497,0.00090526673,0.0009911216,0.0020791604,0.0019736784,0.00008578714],"candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.019703625,0.00009674588,0.00015480333,0.00039490496,0.0010225803,0.0010029987,0.013505157,0.000031218766,0.00018775719],"category_scores_gemma":[0.017103497,0.000063390704,0.0000621308,0.000542002,0.00044545857,0.0059825196,0.0026723598,0.000098420045,0.000024522396],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015582374,0.0001998475,0.002926586,0.000007515595,0.00006222331,0.0000011786399,0.00082020694,0.00032933833,0.00014273796,0.46603444,0.17247264,0.35684747],"study_design_scores_gemma":[0.00051509927,0.000097464435,0.01682417,0.000044034205,0.00003026495,0.000011574461,0.00068073545,0.123702444,0.000037983144,0.20240961,0.65550596,0.00014067454],"about_ca_topic_score_codex":0.00013049401,"about_ca_topic_score_gemma":0.0010888949,"teacher_disagreement_score":0.9095719,"about_ca_system_score_codex":0.000054852797,"about_ca_system_score_gemma":0.00014765309,"threshold_uncertainty_score":0.99183226},"labels":[],"label_agreement":null},{"id":"W2892021733","doi":"10.23889/ijpds.v3i4.842","title":"Patient-Physician Relational Continuity and Health System Utilization Among Albertans","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Emergency department; Medicine; Health care; Continuity of care; Population; Ambulatory care; Multivariate analysis; Family medicine; Disease; Primary care; Nursing; Environmental health","score_opus":0.1871541069187173,"score_gpt":0.5035659731593921,"score_spread":0.3164118662406748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892021733","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80325705,0.00040384187,0.08751001,0.044158764,0.039372295,0.003647437,0.002543195,0.0003241934,0.018783223],"genre_scores_gemma":[0.98793256,0.000037482674,0.0034601681,0.0062486744,0.0013669984,0.000016574613,0.0006598305,0.000013430129,0.00026425355],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99736786,0.00013281366,0.00084345497,0.00039503755,0.0008614463,0.00039939274],"domain_scores_gemma":[0.9969892,0.0002162593,0.0008704191,0.00032861473,0.0013549395,0.00024060433],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0024002134,0.0001160911,0.0001941655,0.00028860717,0.0025600458,0.00010209636,0.00066951953,0.000068020025,0.0000516476],"category_scores_gemma":[0.0005034606,0.00010271401,0.000031763746,0.0002708026,0.00022795908,0.0025612463,0.00036561402,0.00026222918,0.00002650413],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000119750934,0.000045471665,0.7545099,0.000079635014,0.00003847942,0.000001970217,0.0019014165,0.000013611322,0.000056777437,0.13106385,0.041011922,0.07115718],"study_design_scores_gemma":[0.0006651758,0.000119038195,0.8876832,0.00023242614,0.000010676267,0.000018937548,0.0008896987,0.013021321,0.000007411643,0.0012944918,0.09591377,0.00014381445],"about_ca_topic_score_codex":0.0010951315,"about_ca_topic_score_gemma":0.0016907428,"teacher_disagreement_score":0.18467554,"about_ca_system_score_codex":0.0010806367,"about_ca_system_score_gemma":0.0012601262,"threshold_uncertainty_score":0.99873847},"labels":[],"label_agreement":null},{"id":"W2892027396","doi":"10.23889/ijpds.v3i4.956","title":"How do we enhance linked administrative data based chronic disease surveillance in Canada? Results of an environmental scan.","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Public Health Agency of Canada; Manitoba Health; University of Toronto; Ministry of Health; University of Manitoba; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Population; Grey literature; MEDLINE; Psychology; Environmental health; Political science","score_opus":0.06865702117925102,"score_gpt":0.39347320053273227,"score_spread":0.3248161793534813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892027396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9799637,0.0005184131,0.00209505,0.004977152,0.0016340633,0.00041794998,0.01037404,0.0000061857886,0.000013427612],"genre_scores_gemma":[0.99407935,0.000236479,0.0014941203,0.00008019527,0.00059779716,0.0000025149666,0.0034758667,0.000007161845,0.000026507732],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975666,0.000054850003,0.000428914,0.00048741905,0.0012334427,0.00022881768],"domain_scores_gemma":[0.9981026,0.000079347556,0.00032072686,0.00095090235,0.0002016451,0.000344789],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013305297,0.000099914694,0.00017502926,0.00017822698,0.00013791461,0.0000849836,0.0012880099,0.00002385101,0.000019936133],"category_scores_gemma":[0.0010776978,0.00008454209,0.000034613793,0.00018909911,0.00021709336,0.0012806153,0.00018212217,0.00013834925,7.6305105e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007304567,0.00053834537,0.6777812,0.00012389234,0.00017922743,0.0002374795,0.00022580502,0.0011216543,0.0054373057,0.00012741279,0.0031121797,0.30381092],"study_design_scores_gemma":[0.0018664466,0.00017111242,0.8939636,0.00016657713,0.000016425869,0.000043199027,0.00009631147,0.08882531,0.00047324048,0.000033676482,0.014229973,0.000114178816],"about_ca_topic_score_codex":0.05537736,"about_ca_topic_score_gemma":0.37663758,"teacher_disagreement_score":0.3212602,"about_ca_system_score_codex":0.0010268898,"about_ca_system_score_gemma":0.005326141,"threshold_uncertainty_score":0.95091295},"labels":[],"label_agreement":null},{"id":"W2892056745","doi":"10.23889/ijpds.v3i4.857","title":"Validating the accuracy of place of death in Vital Statistics of Calgary Zone residents in 2015","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Palliative Care and End-of-Life Issues","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"","keywords":"Medicine; Place of death; Vital signs; Nursing homes; Emergency department; Medical emergency; Cause of death; Health statistics; Descriptive statistics; Palliative care; Emergency medicine; Nursing; Statistics; Population; Environmental health; Disease","score_opus":0.23209412050459283,"score_gpt":0.5299538748979122,"score_spread":0.2978597543933194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892056745","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97925043,0.0000959614,0.0195934,0.00017847694,0.00033896798,0.00011981943,0.00034708984,0.0000010491616,0.000074781194],"genre_scores_gemma":[0.97241455,0.00007694792,0.027268758,0.000020625503,0.000070439135,7.8867913e-7,0.00012062896,0.000003112462,0.000024124174],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99845564,0.00003112366,0.00060604926,0.000111994785,0.00070726994,0.00008791546],"domain_scores_gemma":[0.99793327,0.00042034083,0.0005873163,0.00018564693,0.00084358396,0.00002983697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001308584,0.00004778274,0.00015150191,0.00027436795,0.000027025875,0.00001101189,0.0005959011,0.000019035275,0.000018230114],"category_scores_gemma":[0.0054464955,0.000035269346,0.000019655936,0.00024572053,0.00019579956,0.0005444964,0.00014769993,0.000079828584,3.7230427e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002563872,0.00008539471,0.98160654,0.000032577293,0.000020331086,0.000004176484,0.00088537065,0.00015896627,0.0098487055,0.0027384695,0.00034054948,0.004022558],"study_design_scores_gemma":[0.0012171742,0.00017017231,0.9540648,0.0012497806,0.000017998316,0.000022354989,0.0004103323,0.025475712,0.015611552,0.0014742311,0.00023388176,0.00005202469],"about_ca_topic_score_codex":0.0019439535,"about_ca_topic_score_gemma":0.00042464933,"teacher_disagreement_score":0.027541729,"about_ca_system_score_codex":0.00007754584,"about_ca_system_score_gemma":0.0002037856,"threshold_uncertainty_score":0.6520358},"labels":[],"label_agreement":null},{"id":"W2892069872","doi":"10.23889/ijpds.v3i4.803","title":"Public housing and healthcare use: Determining whether public housing functions as an intervention using linked population-based administrative data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Government of Alberta; University of Winnipeg","funders":"","keywords":"Public housing; Population; Health care; Cohort; Rate ratio; Generalized estimating equation; Public health; Government (linguistics); Socioeconomic status; Negative binomial distribution; Poisson regression; Subsidized housing; Subsidy; Business; Medicine; Environmental health; Poisson distribution; Economics; Economic growth; Statistics; Nursing","score_opus":0.5025971440767816,"score_gpt":0.5301193650354686,"score_spread":0.02752222095868706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892069872","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9373764,0.000049320286,0.044521328,0.012425893,0.0044850092,0.0003985388,0.0006128771,0.00007631863,0.000054338012],"genre_scores_gemma":[0.98110765,0.000020643716,0.014889121,0.0011856612,0.0014728676,0.000004282152,0.0012558718,0.00002029867,0.000043586835],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9965409,0.00031147822,0.0007045995,0.0006661495,0.0012125049,0.00056433905],"domain_scores_gemma":[0.9964137,0.00031028962,0.00065841037,0.00060802436,0.0015073007,0.0005022577],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0044570905,0.0001575374,0.00017874707,0.00055697793,0.0042253374,0.00391432,0.0017979693,0.000103754865,0.00010144786],"category_scores_gemma":[0.0054869778,0.00015922765,0.000044370787,0.0005433371,0.00046775534,0.01545284,0.00041448913,0.0002257512,0.0000030804035],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000066895685,0.00011035978,0.9016652,0.00002411735,0.00003275982,0.0000046308846,0.000977556,0.000059940416,0.000031623862,0.015853738,0.00015416193,0.081019],"study_design_scores_gemma":[0.0011236739,0.00023674285,0.6651425,0.0004681249,0.000049611015,0.000060446207,0.0052131163,0.29737842,0.0000063795264,0.00399308,0.025798155,0.0005297386],"about_ca_topic_score_codex":0.021481672,"about_ca_topic_score_gemma":0.055229407,"teacher_disagreement_score":0.2973185,"about_ca_system_score_codex":0.00060772686,"about_ca_system_score_gemma":0.001577971,"threshold_uncertainty_score":0.99831754},"labels":[],"label_agreement":null},{"id":"W2892093506","doi":"10.23889/ijpds.v3i4.632","title":"Interactive Data Visualization of Patient Experience and Inpatient Datasets using Tableau Desktop","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Presentation (obstetrics); Data science; Data visualization; Relation (database); Variety (cybernetics); Software; Interactive visualization; Information retrieval; Data mining; Medicine; Artificial intelligence","score_opus":0.23327264590530367,"score_gpt":0.5834559677525409,"score_spread":0.35018332184723727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892093506","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.936729,0.00006842098,0.048358433,0.00080449844,0.008012213,0.0006759949,0.0051089656,0.000022488224,0.00021994772],"genre_scores_gemma":[0.9824563,0.00006708221,0.012114181,0.0016024795,0.00046104527,0.0000065603917,0.0032671525,0.000009990854,0.0000151785125],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975337,0.00011172848,0.0008210586,0.0004549565,0.0007989511,0.00027964343],"domain_scores_gemma":[0.9967755,0.00023966242,0.0008983903,0.00078163657,0.0011642484,0.00014053493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015119358,0.00010161853,0.00016159505,0.00031662497,0.0010085017,0.00007661933,0.002116935,0.00004707977,0.000121494],"category_scores_gemma":[0.0021453043,0.00008772852,0.000013062556,0.00028094393,0.0002610396,0.0049179695,0.0024151497,0.00015796823,0.000004229843],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011932306,0.00034837425,0.807584,0.00017497572,0.000117884374,0.0000089425075,0.015331143,0.00011001309,0.0068084775,0.011334964,0.041921124,0.11506691],"study_design_scores_gemma":[0.0034163136,0.00079791405,0.32266286,0.0011309383,0.00011147274,0.00016329876,0.0074220286,0.34577945,0.001496853,0.004091672,0.31211552,0.00081166986],"about_ca_topic_score_codex":0.0010368275,"about_ca_topic_score_gemma":0.00022884109,"teacher_disagreement_score":0.4849211,"about_ca_system_score_codex":0.0004056014,"about_ca_system_score_gemma":0.0008613439,"threshold_uncertainty_score":0.7756682},"labels":[],"label_agreement":null},{"id":"W2892116193","doi":"10.23889/ijpds.v3i4.992","title":"Advancing data collection of hospital-related harms: Results from hospital discharges dually coded with ICD-10 and ICD-11","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"ICD-10; Medicine; Coding (social sciences); Adverse effect; Medical emergency; Diagnosis code; Harm; Emergency medicine; Statistics; Internal medicine; Psychology; Psychiatry; Population","score_opus":0.1284633237970884,"score_gpt":0.4645192322549255,"score_spread":0.33605590845783706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892116193","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94929135,0.00003769285,0.026771035,0.012464241,0.006652585,0.0007615341,0.0035905016,0.000052472104,0.00037859267],"genre_scores_gemma":[0.9780648,0.00009769627,0.016199935,0.00025287006,0.00075055344,0.000008778705,0.0042703254,0.000011695041,0.00034337142],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969258,0.00008856059,0.0011365394,0.0004409111,0.0010750423,0.0003331816],"domain_scores_gemma":[0.9959008,0.00047491136,0.0013043536,0.0005831709,0.0014976813,0.0002390676],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0037481033,0.00012189495,0.00019972691,0.00027688977,0.001390091,0.00009666441,0.0013524164,0.00009229784,0.0001550826],"category_scores_gemma":[0.0059589036,0.00009322091,0.000015403077,0.00035075197,0.00029154273,0.003943899,0.0005556661,0.00032150274,0.000016883072],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0051799715,0.00072669727,0.63166034,0.00032154197,0.00037343233,0.000014302673,0.0332122,0.00029009205,0.0017296606,0.010945976,0.26901224,0.04653357],"study_design_scores_gemma":[0.008912712,0.0015907058,0.58773047,0.002291146,0.000094936084,0.000023943332,0.003772139,0.33743683,0.00017961205,0.0035027857,0.053928405,0.00053633197],"about_ca_topic_score_codex":0.0012289573,"about_ca_topic_score_gemma":0.0006324246,"teacher_disagreement_score":0.33714673,"about_ca_system_score_codex":0.00018537688,"about_ca_system_score_gemma":0.00067996787,"threshold_uncertainty_score":0.99990994},"labels":[],"label_agreement":null},{"id":"W2892120025","doi":"10.23889/ijpds.v3i4.629","title":"Evaluating area-based socioeconomic status predictors of pediatric health outcomes in Manitoba","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"","keywords":"Socioeconomic status; Medicine; Demography; Index (typography); Categorical variable; Population; Inequality; Environmental health; Gerontology; Statistics; Mathematics","score_opus":0.1972869403847135,"score_gpt":0.5077860256525099,"score_spread":0.31049908526779635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892120025","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98716784,0.00004478084,0.0010450289,0.005965518,0.0050315056,0.00028740114,0.0003225463,0.000014024657,0.00012136614],"genre_scores_gemma":[0.99339795,0.00009079265,0.004535219,0.00090691086,0.0009509078,0.0000049440764,0.000073405135,0.0000056692475,0.000034214692],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975378,0.00010456612,0.00068383856,0.00024713317,0.000983963,0.0004427274],"domain_scores_gemma":[0.9981541,0.00033620148,0.0005928781,0.00019683957,0.00051338004,0.00020660098],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055551208,0.00007454722,0.00016740755,0.0004378446,0.00070165226,0.00018215178,0.0012440713,0.000035090558,0.00010460811],"category_scores_gemma":[0.0025340978,0.000069629656,0.000044037217,0.00022683248,0.0002690917,0.001463816,0.000112499634,0.000104168415,0.0000050202],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018114959,0.000032338176,0.9914939,0.000007979423,0.000005044536,2.3095296e-7,0.0006526419,0.0002185724,0.0000015730999,0.0023520011,0.00051560096,0.004702041],"study_design_scores_gemma":[0.0005262741,0.00006902944,0.9840568,0.000026337626,0.0000047254316,5.920987e-7,0.0010390253,0.010832092,0.0000030536619,0.0011939016,0.0021731842,0.00007500582],"about_ca_topic_score_codex":0.015276874,"about_ca_topic_score_gemma":0.024378944,"teacher_disagreement_score":0.010613519,"about_ca_system_score_codex":0.00084177824,"about_ca_system_score_gemma":0.002379463,"threshold_uncertainty_score":0.9934236},"labels":[],"label_agreement":null},{"id":"W2892138780","doi":"10.23889/ijpds.v3i4.999","title":"Perspectives on Linkage Involving Indigenous data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University nuhelot'ine thaiyots'i nistameyimâkanak Blue Quills; Providence Health Care; Laurentian University","funders":"","keywords":"Indigenous; Sovereignty; Population; Metis; Political science; Sociology; Geography; Public relations; Law; Politics; Database","score_opus":0.46462911489124337,"score_gpt":0.5578686461454321,"score_spread":0.09323953125418871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892138780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4659334,0.00036422446,0.46121588,0.019009322,0.033506203,0.0013475588,0.011367992,0.00017392085,0.007081481],"genre_scores_gemma":[0.97941643,0.00007464351,0.015740056,0.0010105233,0.002048389,0.0000025063505,0.00092062517,0.000009442165,0.0007773726],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.994228,0.00009974058,0.00071321207,0.0010158432,0.0036471914,0.0002959886],"domain_scores_gemma":[0.9945628,0.0005482194,0.00057725987,0.0025243151,0.0016270188,0.00016040125],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.014770442,0.000117667514,0.0001394222,0.00081864203,0.001090636,0.0028769954,0.016121648,0.000033821045,0.00027382124],"category_scores_gemma":[0.017519932,0.000090278714,0.000037625683,0.0007125098,0.00042339964,0.008805948,0.0034405973,0.00016815141,0.00026867137],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039640674,0.00065137574,0.018122258,0.000006377504,0.00016241566,0.000038245627,0.010247961,0.00039813077,0.0008695862,0.26379633,0.18237679,0.52293414],"study_design_scores_gemma":[0.0011503472,0.000427871,0.105182394,0.00011620075,0.00003191921,0.00011424159,0.011960764,0.10811634,0.00015654862,0.10448974,0.6677022,0.0005513984],"about_ca_topic_score_codex":0.00016859727,"about_ca_topic_score_gemma":0.00026357576,"teacher_disagreement_score":0.52238274,"about_ca_system_score_codex":0.00017465542,"about_ca_system_score_gemma":0.00022261798,"threshold_uncertainty_score":0.9981581},"labels":[],"label_agreement":null},{"id":"W2892160487","doi":"10.23889/ijpds.v3i4.979","title":"Bias, accuracy and sample size in the systematic linking of historical records","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"St. Francis Xavier University; University of Guelph","funders":"","keywords":"Representativeness heuristic; Computer science; Sampling bias; Sample size determination; Data quality; Invariant (physics); Data mining; Sample (material); Selection bias; Statistics; Econometrics; Artificial intelligence; Mathematics","score_opus":0.25332975463957746,"score_gpt":0.4503384809297971,"score_spread":0.19700872629021965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892160487","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91621965,0.0000661666,0.07674188,0.0025183086,0.003404945,0.00073669513,0.0001564314,0.000020293359,0.00013559559],"genre_scores_gemma":[0.9465586,0.000013817171,0.052941684,0.000075229465,0.0003513415,0.000005061645,0.000026078333,0.0000051196344,0.000023057999],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982099,0.000078093646,0.00068043696,0.00017287527,0.0007413375,0.000117387404],"domain_scores_gemma":[0.9946106,0.0038560245,0.00065263856,0.00031239912,0.00053198385,0.000036325597],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004079155,0.000070811046,0.00014837134,0.0002056886,0.00022599057,0.0001641421,0.000989965,0.000028724733,0.000017938304],"category_scores_gemma":[0.032266404,0.000048734808,0.000028098835,0.00028202112,0.00007997182,0.001108759,0.000119890596,0.00009047067,7.7950614e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027573414,0.0004830319,0.6077721,0.0022687726,0.000092870796,0.0000073416377,0.007877603,0.00020856659,0.0009506219,0.33963037,0.0068437485,0.03358925],"study_design_scores_gemma":[0.0011262861,0.00017965282,0.2596345,0.0025283336,0.000078371704,0.00033502467,0.00037870338,0.20992443,0.0000692217,0.522617,0.0028348141,0.0002937121],"about_ca_topic_score_codex":0.00030624756,"about_ca_topic_score_gemma":0.0002641118,"teacher_disagreement_score":0.3481376,"about_ca_system_score_codex":0.00019310982,"about_ca_system_score_gemma":0.00006233787,"threshold_uncertainty_score":0.9758852},"labels":[],"label_agreement":null},{"id":"W2892165384","doi":"10.23889/ijpds.v3i4.770","title":"Linking lab, program, and administrative data to provide comprehensive colorectal cancer screening status of patients to primary care providers in Calgary, Alberta","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Calgary Laboratory Services; Alberta Medical Association; Alberta Health Services","funders":"","keywords":"Medicine; Colonoscopy; Family medicine; Colorectal cancer; Guideline; Cancer screening; Primary care; Test (biology); Cohort; Point of care; Cancer; Internal medicine; Nursing; Pathology","score_opus":0.09827326742823175,"score_gpt":0.42102323333623165,"score_spread":0.32274996590799987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892165384","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99454117,0.000057844216,0.0021581093,0.00044574216,0.00072769576,0.001263549,0.00070921105,0.00001434891,0.0000823061],"genre_scores_gemma":[0.9604479,0.000012182659,0.037550457,0.00026749217,0.00022796831,0.00003926225,0.0014287184,0.0000102938675,0.000015743068],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998046,0.000025512376,0.00039948247,0.00051029434,0.00074500445,0.00027372644],"domain_scores_gemma":[0.9977631,0.00008263895,0.0002264587,0.0002777888,0.0013966436,0.00025334998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002928251,0.00011310868,0.00018079253,0.00039034008,0.00017823953,0.0001644655,0.00064454816,0.000036090325,0.00000576377],"category_scores_gemma":[0.00088254205,0.00010315971,0.00001846273,0.00045926552,0.00014325853,0.0012715962,0.0006746018,0.00014224403,6.171983e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0052969744,0.00008247196,0.5895984,0.000050683993,0.00003735573,0.000003186221,0.0017247582,0.00008863386,0.0016087433,0.000022028247,0.00018876475,0.401298],"study_design_scores_gemma":[0.0013762661,0.0027337368,0.96525806,0.00055964274,0.000027983471,0.000022630216,0.00042243133,0.0150129255,0.0007719373,0.000012937512,0.013660038,0.00014143225],"about_ca_topic_score_codex":0.0061406046,"about_ca_topic_score_gemma":0.013791485,"teacher_disagreement_score":0.40115657,"about_ca_system_score_codex":0.00040031588,"about_ca_system_score_gemma":0.0005846136,"threshold_uncertainty_score":0.9282798},"labels":[],"label_agreement":null},{"id":"W2892166167","doi":"10.23889/ijpds.v3i4.847","title":"Education Outcomes Associated with Full Day Kindergarten Among First Nations Children: A retrospective administrative database cohort study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Numeracy; Graduation (instrument); Medicine; Population; Propensity score matching; Cohort; Reading (process); Test (biology); Demography; Psychology; Pediatrics; Family medicine; Literacy; Environmental health; Pedagogy; Political science","score_opus":0.03821946088335126,"score_gpt":0.40470431598310946,"score_spread":0.3664848550997582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892166167","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9822938,0.0000072861067,0.0015870631,0.00093583664,0.0045386977,0.0019956047,0.00057940994,0.000056479177,0.008005822],"genre_scores_gemma":[0.9945205,0.0000769555,0.0009601527,0.00005197588,0.0013764916,0.000022743192,0.0012902804,0.000014481181,0.0016864466],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9962555,0.00021535717,0.000517465,0.0006244403,0.0019658962,0.00042131275],"domain_scores_gemma":[0.99468213,0.00031912947,0.00075449114,0.00048299183,0.003487422,0.00027380584],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0044447402,0.00017008343,0.00019058715,0.00061089743,0.014061155,0.0007823583,0.0018627375,0.0000671412,0.00013635252],"category_scores_gemma":[0.0012443903,0.00013492764,0.000041515694,0.0009611436,0.000849387,0.0045648078,0.000023656416,0.00021286162,0.000013178047],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025830606,0.0006731046,0.9458188,9.197376e-7,0.00011050227,9.875733e-7,0.024147972,0.0000055740757,6.164713e-7,0.02879351,0.00033587785,0.00008633758],"study_design_scores_gemma":[0.00043027845,0.00025228073,0.9887911,0.00006363034,0.000053696465,0.0000107045125,0.0033795931,0.00018785217,0.0000040827495,0.0006084654,0.006023244,0.0001950526],"about_ca_topic_score_codex":0.035163395,"about_ca_topic_score_gemma":0.89876115,"teacher_disagreement_score":0.86359775,"about_ca_system_score_codex":0.0012419526,"about_ca_system_score_gemma":0.012904706,"threshold_uncertainty_score":0.9926912},"labels":[],"label_agreement":null},{"id":"W2892190501","doi":"10.23889/ijpds.v3i4.1025","title":"Mining Twitter data to #educate the public about #sepsis","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Sepsis; Medicine; Septic shock; Intensive care medicine; Internal medicine","score_opus":0.5336464602701756,"score_gpt":0.5677336899946666,"score_spread":0.034087229724490964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892190501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60822576,0.00006931424,0.0056103943,0.2925812,0.09068469,0.0012382821,0.00022737439,0.00006090306,0.0013021049],"genre_scores_gemma":[0.97077984,0.00005197385,0.012313432,0.0034312983,0.01285365,0.000060565308,0.00028297302,0.00001214433,0.00021414753],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99680567,0.00013885109,0.0004326826,0.00048182072,0.0016705948,0.0004703778],"domain_scores_gemma":[0.9957857,0.0009075614,0.0003508614,0.0009479681,0.0016509902,0.00035693336],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0076209754,0.000088933346,0.000090839625,0.00033409605,0.0028819372,0.0014882034,0.008044581,0.00004565788,0.00021572954],"category_scores_gemma":[0.02846357,0.000071539645,0.000023925391,0.0009322563,0.00067526364,0.004234929,0.0008104488,0.00014468645,0.00008164445],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068043875,0.00015516189,0.20477192,0.000006611376,0.00006248917,0.0000020266052,0.055042822,0.000011919133,0.00024673648,0.031703644,0.3568592,0.3510694],"study_design_scores_gemma":[0.00011082579,0.000024270086,0.10880371,0.000034648456,0.00000968805,0.000008863918,0.0038518494,0.0015271326,0.000009742247,0.0012240567,0.88428146,0.000113767775],"about_ca_topic_score_codex":0.0025043713,"about_ca_topic_score_gemma":0.003821753,"teacher_disagreement_score":0.52742225,"about_ca_system_score_codex":0.00044559434,"about_ca_system_score_gemma":0.0015654602,"threshold_uncertainty_score":0.9995484},"labels":[],"label_agreement":null},{"id":"W2892196296","doi":"10.23889/ijpds.v3i4.627","title":"Comparing five comorbidity indices to predict mortality in chronic kidney disease","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Humber River Regional Hospital; University of Ottawa; Western University; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Comorbidity; Medicine; Kidney disease; Renal function; Dialysis; Internal medicine; Population; Charlson comorbidity index; Logistic regression; Intensive care medicine; Environmental health","score_opus":0.15599911387644233,"score_gpt":0.4554737720692009,"score_spread":0.2994746581927586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892196296","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9897077,0.00002498499,0.0046123792,0.0017274087,0.0022023544,0.00046841416,0.00043679329,0.000031879652,0.00078805996],"genre_scores_gemma":[0.9964839,0.000017203176,0.0010044437,0.0005205275,0.0011335275,0.000010669474,0.0007380972,0.0000071779596,0.000084425374],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979031,0.000016652019,0.00037614885,0.00040075456,0.0010501712,0.00025316986],"domain_scores_gemma":[0.99853015,0.00003189598,0.00016591989,0.00045200798,0.00034249524,0.00047753265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009758404,0.00010221014,0.00013690423,0.00044728414,0.00021001916,0.0003060699,0.0012143691,0.000016864644,0.00017897668],"category_scores_gemma":[0.0011804482,0.000094413794,0.000037438444,0.0003619309,0.00022525025,0.0017924,0.0005356533,0.000116421455,0.000023228211],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003543437,0.00012669315,0.98230034,0.000040908246,0.00005602622,0.00003817107,0.00008998954,0.0012302209,0.00013762497,0.0030719787,0.0097048,0.0028488738],"study_design_scores_gemma":[0.0010734352,0.00007614758,0.88330495,0.00027486734,0.00003826147,0.00001067776,0.00004179383,0.10701446,0.000017659417,0.0011047942,0.006954598,0.00008834658],"about_ca_topic_score_codex":0.000531356,"about_ca_topic_score_gemma":0.00067282066,"teacher_disagreement_score":0.105784245,"about_ca_system_score_codex":0.0008999933,"about_ca_system_score_gemma":0.0010040698,"threshold_uncertainty_score":0.38500828},"labels":[],"label_agreement":null},{"id":"W2892227563","doi":"10.23889/ijpds.v3i4.973","title":"From the back room to the front room: Combining clinical and financial information to support evidence-based decision making","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Activity-based costing; Context (archaeology); Presentation (obstetrics); Health care; Decision support system; Computer science; Business; Finance; Medicine; Marketing; Data mining; Economics","score_opus":0.3148963557034366,"score_gpt":0.5604997145494065,"score_spread":0.2456033588459699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892227563","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30050203,0.0000530824,0.56134814,0.111399315,0.023894744,0.0015836452,0.0009248875,0.00003292263,0.0002612366],"genre_scores_gemma":[0.81849873,0.00003502546,0.05318171,0.12357469,0.0043660756,0.000028856279,0.0002257693,0.000009255469,0.00007987132],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99714035,0.00018204321,0.0010627551,0.00028563602,0.0010051131,0.00032412013],"domain_scores_gemma":[0.99523276,0.0024909442,0.00047104197,0.0005233622,0.001085687,0.00019620395],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.00717366,0.00010368079,0.00015615538,0.00017494756,0.0021412657,0.0003253,0.0021590872,0.00007106454,0.00032446955],"category_scores_gemma":[0.010126811,0.00006189565,0.000042939882,0.00024179422,0.00009437258,0.003102707,0.00091562246,0.00038063663,0.00043510587],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046370816,0.0000123554955,0.24750614,0.0000043488776,0.0000070318474,7.3374053e-7,0.0014904689,0.00008107821,0.0000060209063,0.00043793043,0.35897124,0.39101896],"study_design_scores_gemma":[0.00048718246,0.0001700057,0.6411379,0.00036811375,0.000010346638,0.000003901998,0.00023876429,0.0077789836,0.0000017082051,0.0014702803,0.34824762,0.00008516029],"about_ca_topic_score_codex":0.0004595794,"about_ca_topic_score_gemma":0.0017309734,"teacher_disagreement_score":0.5179967,"about_ca_system_score_codex":0.0003071002,"about_ca_system_score_gemma":0.0015989451,"threshold_uncertainty_score":0.9991578},"labels":[],"label_agreement":null},{"id":"W2892259303","doi":"10.23889/ijpds.v3i4.700","title":"Validation of mechanical ventilation coding in hospital discharge abstracts: a population data linkage study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Respiratory Support and Mechanisms","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Health Sciences Centre; Manitoba Health","funders":"","keywords":"Medicine; Mechanical ventilation; Emergency medicine; Hospital discharge; Intensive care unit; Population; Ventilation (architecture); Psychological intervention; Health care; Gold standard (test); Intensive care medicine; Internal medicine; Nursing","score_opus":0.10170891341035783,"score_gpt":0.42790246838781815,"score_spread":0.32619355497746033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892259303","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9790096,0.000005459471,0.017157368,0.00029623546,0.0026134658,0.0006463483,0.00021547904,0.000017314047,0.000038676317],"genre_scores_gemma":[0.99041104,0.0000064269034,0.006313543,0.000038694452,0.00073395565,0.000005466748,0.0024516343,0.000012925498,0.000026337228],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997087,0.0000364316,0.0009332799,0.0005049068,0.001233388,0.00020496782],"domain_scores_gemma":[0.99778634,0.00004792922,0.0006464984,0.0007295755,0.00067228865,0.000117350864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031099755,0.00011783955,0.00020305952,0.0005541982,0.00018616936,0.00016348527,0.0012681563,0.000058399957,0.00007480769],"category_scores_gemma":[0.0013061567,0.000106838605,0.000037492136,0.0003772225,0.00006368405,0.0037304852,0.00041430147,0.00016461097,0.0000071767136],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087675295,0.0021369655,0.91353506,0.000041987798,0.00011557244,0.000046467652,0.00076184236,0.00016458145,0.051469307,0.0035107983,0.0005062619,0.026834384],"study_design_scores_gemma":[0.002413662,0.0009483922,0.9407436,0.00022534069,0.000080693084,0.000064173124,0.00044883438,0.046396464,0.0064990534,0.0009049384,0.0010786738,0.00019612875],"about_ca_topic_score_codex":0.00020953549,"about_ca_topic_score_gemma":0.000111029345,"teacher_disagreement_score":0.046231885,"about_ca_system_score_codex":0.00015968528,"about_ca_system_score_gemma":0.00016263964,"threshold_uncertainty_score":0.43567517},"labels":[],"label_agreement":null},{"id":"W2892272336","doi":"10.23889/ijpds.v3i4.910","title":"Variation in Access to Specialist Care and Risk of Surgery in Patients with Inflammatory Bowel Disease: A Population-Based Cohort Study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Inflammatory Bowel Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa; Mount Sinai Hospital; Institute for Clinical Evaluative Sciences; Children's Hospital of Eastern Ontario","funders":"","keywords":"Medicine; Inflammatory bowel disease; Internal medicine; Cohort; Odds ratio; Population; Colonoscopy; Logistic regression; Disease; Colorectal cancer; Environmental health","score_opus":0.01642712511394824,"score_gpt":0.3168605782782519,"score_spread":0.3004334531643037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892272336","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99798864,0.0000061433593,0.0005497493,0.000022646851,0.00040425692,0.00060771476,0.00041310175,0.0000027578476,0.0000049679647],"genre_scores_gemma":[0.9985583,0.00000389673,0.00036885243,0.000037145703,0.00018260021,0.000019390065,0.00081910606,0.00000885919,0.0000018795134],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99844337,0.00006998979,0.00040172663,0.00036139868,0.0005902057,0.00013329391],"domain_scores_gemma":[0.9985162,0.00002800507,0.0003054146,0.00032113268,0.00071775523,0.000111510046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087424676,0.00009371893,0.00009321388,0.00041930252,0.00011651185,0.00014334831,0.00059806876,0.000026170088,0.000006867827],"category_scores_gemma":[0.0010864766,0.000087749795,0.000019943369,0.00018383576,0.00006685833,0.00018969862,0.0001922781,0.000049231385,4.175732e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093520293,0.00009801691,0.9961869,0.000008265959,0.00001482122,0.0000036118397,0.00006582829,0.0021146606,0.000034310426,0.0000141907785,0.000023631712,0.00050056627],"study_design_scores_gemma":[0.00084760203,0.00006353771,0.9972375,0.00004786552,0.00001554343,3.1454152e-7,0.000021175985,0.001588992,0.000011585514,0.000029688379,0.000030056895,0.00010613182],"about_ca_topic_score_codex":0.0003302357,"about_ca_topic_score_gemma":0.002461654,"teacher_disagreement_score":0.002131418,"about_ca_system_score_codex":0.000115835166,"about_ca_system_score_gemma":0.00027766824,"threshold_uncertainty_score":0.35783327},"labels":[],"label_agreement":null},{"id":"W2892297510","doi":"10.23889/ijpds.v3i4.709","title":"A National Concept Dictionary","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Computer science; Flexibility (engineering); Coding (social sciences); Population; World Wide Web; Data science; Information retrieval","score_opus":0.07038370525731832,"score_gpt":0.4236048892272687,"score_spread":0.3532211839699504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892297510","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.63578314,0.00049201446,0.3246062,0.008568428,0.024004368,0.00040067613,0.0018960304,0.00008991637,0.0041592186],"genre_scores_gemma":[0.97966075,0.000019511934,0.01564067,0.00058900914,0.002926929,0.0000033271833,0.00077051664,0.0000052447594,0.00038402996],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99876225,0.000013753891,0.00019308802,0.00027583863,0.0006149451,0.00014010123],"domain_scores_gemma":[0.9987175,0.000020362462,0.000115358445,0.00018146887,0.00089024403,0.00007505073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071160734,0.00006060119,0.000047338457,0.00010672179,0.00032502256,0.00011865316,0.0011700585,0.000047189442,0.000043294483],"category_scores_gemma":[0.0014603076,0.00005211945,0.000029329476,0.000107440035,0.00046062842,0.000051840867,0.00028825106,0.00005560384,0.000009559568],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007171164,0.00032683197,0.042040158,0.000006159371,0.00028034975,0.00000916952,0.00029599402,0.00035950865,0.14191477,0.017017279,0.41273752,0.38429514],"study_design_scores_gemma":[0.0010376007,0.00043976615,0.08484849,0.000027896136,0.000010222906,0.0004214485,0.000096061005,0.014881924,0.0056183673,0.005116889,0.88725185,0.0002494972],"about_ca_topic_score_codex":0.000012506782,"about_ca_topic_score_gemma":0.000014535425,"teacher_disagreement_score":0.4745143,"about_ca_system_score_codex":0.000043145756,"about_ca_system_score_gemma":0.0002374219,"threshold_uncertainty_score":0.24998437},"labels":[],"label_agreement":null},{"id":"W2892299255","doi":"10.23889/ijpds.v3i4.623","title":"Development and validation of case-finding algorithms for recurrence of breast cancer using routinely collected administrative data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Breast cancer; Algorithm; Cohort; Cancer; Cancer registry; Mastectomy; Internal medicine; Chart; Cancer recurrence; Oncology; Statistics; Computer science","score_opus":0.5282199424168927,"score_gpt":0.539387428675131,"score_spread":0.011167486258238268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892299255","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93505365,0.00004462263,0.06133436,0.00021666504,0.00068669714,0.00028819285,0.0023568324,0.0000042396236,0.000014752428],"genre_scores_gemma":[0.8481744,0.000010901834,0.15115206,0.000024115436,0.00023663869,0.0000031504585,0.00038534155,0.0000039466045,0.0000094769175],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847835,0.000011710788,0.0005056674,0.00029138205,0.0005780125,0.00013489705],"domain_scores_gemma":[0.9972545,0.0000681008,0.00056326756,0.00023158379,0.0018027475,0.000079831465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012068234,0.00007465068,0.0001484977,0.00020000467,0.00027354373,0.000071906135,0.0005832807,0.000026442583,0.000016584247],"category_scores_gemma":[0.000733733,0.00006617079,0.000016232238,0.0003099381,0.00018410505,0.0014014302,0.00022946554,0.00005500064,9.4961905e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038071845,0.00035129214,0.56110775,0.00027289925,0.0007249266,0.00009343121,0.0042097615,0.00054980535,0.0731762,0.0032018179,0.0019966175,0.35050833],"study_design_scores_gemma":[0.0036607797,0.000530139,0.28168383,0.0022399405,0.00031172662,0.010567755,0.0022574523,0.6485127,0.047024045,0.0004143125,0.0023951284,0.0004021635],"about_ca_topic_score_codex":0.00048732854,"about_ca_topic_score_gemma":0.00020952034,"teacher_disagreement_score":0.6479629,"about_ca_system_score_codex":0.00016748192,"about_ca_system_score_gemma":0.0008699304,"threshold_uncertainty_score":0.26983663},"labels":[],"label_agreement":null},{"id":"W2892303453","doi":"10.23889/ijpds.v3i4.659","title":"Using administrative data to examine mental health service use among post-secondary students in Alberta, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mental health; Government (linguistics); Service (business); Psychology; Medicine; Psychiatry; Business","score_opus":0.2734236201072307,"score_gpt":0.5203516845988259,"score_spread":0.24692806449159516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892303453","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96265906,0.000010756354,0.00021408,0.030038584,0.0041272263,0.00042417782,0.0024400018,0.000005495049,0.000080639074],"genre_scores_gemma":[0.9829171,0.000016465712,0.0032723392,0.012172295,0.000551411,0.0000021373935,0.00084531424,0.000006805575,0.00021618174],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970387,0.00010209665,0.0005070386,0.00040618505,0.001505282,0.0004406914],"domain_scores_gemma":[0.9980869,0.0001997185,0.00027894857,0.000390713,0.0006259335,0.00041777184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026480223,0.00009232346,0.00013267143,0.00019608399,0.0012141988,0.00072206714,0.003652259,0.000026464868,0.000104134924],"category_scores_gemma":[0.0019203523,0.00009118863,0.0000111038935,0.00043019708,0.00014776799,0.005098763,0.0007975937,0.00012971452,0.0000027811666],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007272388,0.0000613306,0.98282874,0.000009184028,0.000017203161,0.000005565585,0.004163602,0.0000393711,0.000011866385,0.0017200863,0.008100995,0.0029693465],"study_design_scores_gemma":[0.00029022933,0.000033289594,0.9322651,0.00009774699,0.0000021769533,0.0000087325225,0.0024492014,0.004034981,0.000002386642,0.000042446496,0.060665652,0.000108044354],"about_ca_topic_score_codex":0.98374194,"about_ca_topic_score_gemma":0.99811566,"teacher_disagreement_score":0.05256466,"about_ca_system_score_codex":0.0012180082,"about_ca_system_score_gemma":0.0056753755,"threshold_uncertainty_score":0.9999615},"labels":[],"label_agreement":null},{"id":"W2892336390","doi":"10.23889/ijpds.v3i4.816","title":"Concordance of EDI-based prevalence rates of health disorders with administrative data in two Canadian provinces","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child and Adolescent Health","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University","funders":"","keywords":"Concordance; Autism spectrum disorder; Autism; Medicine; Anxiety; Prevalence; Psychiatry; Pediatrics; Environmental health; Population","score_opus":0.18390914830788038,"score_gpt":0.551178769258648,"score_spread":0.36726962095076754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892336390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9631816,0.00019567572,0.010442674,0.014708367,0.002923358,0.0017354807,0.0064343815,0.00001325339,0.00036517534],"genre_scores_gemma":[0.994064,0.000057723566,0.004653939,0.000473434,0.00024412166,0.0000021427893,0.00047197263,0.000005990398,0.000026691452],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99772584,0.00015373222,0.00078845985,0.00034937,0.0006313867,0.00035121926],"domain_scores_gemma":[0.9974059,0.00022535636,0.0010195365,0.00051355374,0.0006634528,0.0001722034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003536285,0.00008609031,0.00017935605,0.00031916433,0.00053460465,0.000024172972,0.0020750023,0.000020061712,0.000045059518],"category_scores_gemma":[0.0009494582,0.000067414985,0.000011736126,0.00035220588,0.00043076137,0.0013379022,0.0001853944,0.00020882784,0.0000014742772],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018243032,0.00006666643,0.98945326,0.00011399492,0.0000062761414,4.777897e-7,0.00052901363,0.0000496207,0.00002171099,0.002119991,0.0005324386,0.006924094],"study_design_scores_gemma":[0.0014009655,0.00031157906,0.9693156,0.0019117063,0.000004885287,0.000003533448,0.0010107671,0.022844527,0.00004168513,0.00058473105,0.0024641592,0.00010589278],"about_ca_topic_score_codex":0.0853506,"about_ca_topic_score_gemma":0.5679781,"teacher_disagreement_score":0.48262748,"about_ca_system_score_codex":0.00031072533,"about_ca_system_score_gemma":0.008898181,"threshold_uncertainty_score":0.99672043},"labels":[],"label_agreement":null},{"id":"W2892341091","doi":"10.23889/ijpds.v3i4.625","title":"Prevalence and incidence of diagnosed hypertension in Alberta, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Incidence (geometry); Population; Health care; Estimation; Timeline; Demography; Psychological intervention; Public health; Family medicine; Environmental health; Pediatrics; Geography","score_opus":0.06724514181942795,"score_gpt":0.4009796097472367,"score_spread":0.3337344679278087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892341091","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9923113,0.00004895243,0.00028189196,0.0057583665,0.001248438,0.00020709453,0.000066864486,0.0000021910575,0.0000748816],"genre_scores_gemma":[0.9977655,0.00008027974,0.0011675018,0.0006043671,0.00027824863,0.0000020695998,0.000030184465,0.000003412748,0.00006845083],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984757,0.000027036556,0.0004313623,0.00021511248,0.00069200445,0.00015881774],"domain_scores_gemma":[0.9983594,0.00017494426,0.00019940961,0.00021928339,0.00086842553,0.00017853582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015193414,0.000051479925,0.000120917226,0.00019055407,0.0001078964,0.000033874217,0.00040792773,0.000025024972,0.000018532972],"category_scores_gemma":[0.0032943545,0.00004172139,0.00000905708,0.00020320246,0.000111653724,0.0007462446,0.00010369655,0.00008921616,5.453029e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059904945,0.000025598836,0.97974706,0.000064850195,0.000004540497,0.0000146362945,0.00012921981,0.0000033105607,0.0002927165,0.0011235172,0.0010116166,0.017523047],"study_design_scores_gemma":[0.0004301241,0.00009508853,0.9818544,0.0003331172,0.0000031886311,0.00035919258,0.000037572176,0.012090009,0.00004384254,0.00012687208,0.0045842286,0.000042382053],"about_ca_topic_score_codex":0.7745289,"about_ca_topic_score_gemma":0.6581857,"teacher_disagreement_score":0.11634323,"about_ca_system_score_codex":0.00020956539,"about_ca_system_score_gemma":0.0024896662,"threshold_uncertainty_score":0.4416561},"labels":[],"label_agreement":null},{"id":"W2892364303","doi":"10.23889/ijpds.v3i4.1010","title":"Identifying and Prioritizing Low Value Care in British Columbia Using Three Administrative Health Data Assets","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare cost, quality, practices","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; University of Calgary","funders":"","keywords":"Disinvestment; Health care; Health technology; Business; Excellence; Fiscal year; Operations management; Medicine; Finance; Incentive; Political science; Engineering; Economics","score_opus":0.8128299546670057,"score_gpt":0.6662634596807558,"score_spread":0.14656649498624985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892364303","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9808136,0.00032954788,0.008697569,0.0023140153,0.00490008,0.00079357316,0.0020828347,0.00002626571,0.00004250803],"genre_scores_gemma":[0.9667777,0.00012976404,0.029901031,0.0011680746,0.0011539548,0.0000071598706,0.0008179313,0.00001738554,0.000027009162],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9958773,0.0005741091,0.0011311164,0.000745387,0.0011354142,0.0005366576],"domain_scores_gemma":[0.996009,0.00056315673,0.0010977872,0.00068850064,0.0013519758,0.00028960683],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009841119,0.000100627265,0.00022681811,0.00022250958,0.002795303,0.0011787567,0.0022086846,0.00008615317,0.000045304158],"category_scores_gemma":[0.005958114,0.00014443959,0.00001716702,0.0003890285,0.00027813445,0.007753512,0.0015051676,0.00063959055,0.0000057431716],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038268397,0.00004066041,0.945571,0.00015551197,0.000016200884,0.000022319355,0.002058193,0.000004079541,0.000111142246,0.00059724,0.0007185174,0.05066687],"study_design_scores_gemma":[0.00079510425,0.000099019104,0.9614758,0.0018587286,0.000009679327,0.00018763325,0.005224221,0.024342677,0.0000016766807,0.0022520553,0.003567921,0.00018549684],"about_ca_topic_score_codex":0.09437407,"about_ca_topic_score_gemma":0.5901181,"teacher_disagreement_score":0.49574405,"about_ca_system_score_codex":0.0009837889,"about_ca_system_score_gemma":0.0032195544,"threshold_uncertainty_score":0.99985814},"labels":[],"label_agreement":null},{"id":"W2892370412","doi":"10.23889/ijpds.v3i4.694","title":"Automated Referral to Cardiac Rehabilitation following Coronary Artery Bypass Grafting is associated with limited improvements in program completion: a large cohort study","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cardiac Health and Mental Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Referral; Medicine; Rehabilitation; Cohort; Hazard ratio; Coronary artery disease; Bypass grafting; Population; Emergency medicine; Artery; Internal medicine; Physical therapy; Confidence interval; Family medicine","score_opus":0.05807947859956375,"score_gpt":0.44546878312761895,"score_spread":0.3873893045280552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892370412","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928315,0.0000045631923,0.00014159184,0.0011072975,0.0021968873,0.003260493,0.0002721622,0.00011271258,0.000072744384],"genre_scores_gemma":[0.9927248,0.0000017472628,0.004811691,0.00084444124,0.0002828752,0.00012368555,0.0011697278,0.00001661841,0.000024448784],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99632245,0.00008009308,0.00070139475,0.00056287315,0.0018200444,0.0005131207],"domain_scores_gemma":[0.99764585,0.00009703734,0.00028200474,0.00037156141,0.001231373,0.00037215432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005258243,0.00014103824,0.00030161522,0.00070213206,0.00058855134,0.00017991725,0.0004519349,0.000040172836,0.000010751349],"category_scores_gemma":[0.0013396483,0.00012447606,0.000060328406,0.0010829219,0.00009775518,0.0013177608,0.0002033,0.00019392929,0.0000058926557],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004732621,0.00061496755,0.9919754,0.000008167248,0.00008358183,0.000017403687,0.000696035,0.0000050110352,0.00042192772,0.000015333804,0.00056705193,0.005121813],"study_design_scores_gemma":[0.003240302,0.0023826205,0.97189945,0.00024317783,0.00005452933,0.00005019788,0.0006914475,0.02068248,0.000016908245,0.000015903459,0.0006023166,0.000120683784],"about_ca_topic_score_codex":0.000367207,"about_ca_topic_score_gemma":0.00034604277,"teacher_disagreement_score":0.020677468,"about_ca_system_score_codex":0.0016232914,"about_ca_system_score_gemma":0.0006278844,"threshold_uncertainty_score":0.50759864},"labels":[],"label_agreement":null},{"id":"W2892376969","doi":"10.23889/ijpds.v3i4.878","title":"Integrating population-wide laboratory testing data with physician audit-and-feedback reports to improve glycemic and cholesterol control among Ontarians with diabetes","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Vector Institute; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Diabetes mellitus; Glycemic; Interquartile range; Glycated hemoglobin; Population; Audit; Diabetes management; Test (biology); Internal medicine; Family medicine; Emergency medicine; Type 2 diabetes; Environmental health; Endocrinology; Accounting","score_opus":0.09425001951158105,"score_gpt":0.4291756410301852,"score_spread":0.33492562151860417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892376969","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97122854,0.000008691053,0.023423798,0.0036463523,0.0006273505,0.00063813425,0.00037456866,0.000029545674,0.000023009186],"genre_scores_gemma":[0.94586927,0.0000018041486,0.050234873,0.0022022536,0.00091390824,0.000011087743,0.0007340555,0.00002111253,0.000011613262],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99725175,0.000036597456,0.0008569425,0.00072802213,0.0008647493,0.0002619294],"domain_scores_gemma":[0.99572,0.00064161664,0.00096438936,0.0007099722,0.0017129203,0.000251068],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0021884139,0.0001684324,0.00022987714,0.00022516465,0.0004226132,0.0005186748,0.00056738296,0.000036208745,0.000007528244],"category_scores_gemma":[0.0108692655,0.00012584087,0.0000121614585,0.00036474236,0.00025764186,0.004665502,0.00034205872,0.00024164854,0.000001395313],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040146834,0.000036356218,0.97002685,0.000010289536,0.00006646293,0.0000112888865,0.00006439058,0.000057001642,0.0027586066,0.000052584044,0.00031998762,0.026194721],"study_design_scores_gemma":[0.0020456747,0.0007924086,0.9457158,0.00043180786,0.00015796912,0.00015381671,0.00025806954,0.049186736,0.00008315292,0.00018488307,0.00080838136,0.00018130266],"about_ca_topic_score_codex":0.0017064146,"about_ca_topic_score_gemma":0.0038939575,"teacher_disagreement_score":0.049129736,"about_ca_system_score_codex":0.00016242158,"about_ca_system_score_gemma":0.0003388083,"threshold_uncertainty_score":0.99746263},"labels":[],"label_agreement":null},{"id":"W2892680868","doi":"10.23889/ijpds.v3i4.880","title":"Adherence And Persistence To Antidepressant Medication During Pregnancy: Does It Differ By The Class Of Antidepressant Medication Prescribed?","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal Mental Health During Pregnancy and Postpartum","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Antidepressant; Medicine; Medical prescription; Pregnancy; Depression (economics); Population; Internal medicine; Cohort; Psychiatry; Pediatrics; Pharmacology; Anxiety","score_opus":0.061159640442121244,"score_gpt":0.3773627153100612,"score_spread":0.31620307486793997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892680868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9825148,0.00039119704,0.0031215255,0.010676616,0.0021404764,0.0006531778,0.0003634062,0.000018315961,0.000120479184],"genre_scores_gemma":[0.9971129,0.00050962355,0.0012554124,0.00035623767,0.00029988054,0.000023244304,0.0001101721,0.00000914117,0.00032343558],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99759555,0.000043283548,0.0005666212,0.00041116864,0.0011401614,0.00024321661],"domain_scores_gemma":[0.9982301,0.0001024688,0.000422919,0.00048772828,0.0005340273,0.00022278416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077505293,0.00011909479,0.00016268928,0.00016669711,0.00044935173,0.00010881164,0.0010864682,0.000043215692,0.000056741414],"category_scores_gemma":[0.0007372674,0.00007336673,0.000031658026,0.0001589402,0.00042929163,0.00097025064,0.00034592848,0.00014517011,0.0000037172126],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021195626,0.0004859736,0.8560771,0.0013852995,0.00021309721,0.000024194493,0.004540911,0.000022776192,0.08803209,0.002273199,0.00506662,0.039759178],"study_design_scores_gemma":[0.0010778516,0.0003149461,0.95294714,0.005955667,0.0000644625,0.0004654951,0.00022810674,0.006439723,0.029208979,0.00039957455,0.0027359393,0.00016211292],"about_ca_topic_score_codex":0.00018103336,"about_ca_topic_score_gemma":0.000052258954,"teacher_disagreement_score":0.09687004,"about_ca_system_score_codex":0.0000805751,"about_ca_system_score_gemma":0.000107842825,"threshold_uncertainty_score":0.34560955},"labels":[],"label_agreement":null},{"id":"W2895262614","doi":"10.23889/ijpds.v3i3.437","title":"Challenges Associated with Cross-Jurisdictional Analyses using Administrative Health Data and Primary Care Electronic Medical Records in Canada","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; University of Calgary; University of Manitoba; Alberta Health Services; University of British Columbia; Manitoba Health","funders":"","keywords":"Custodians; Jurisdiction; Business; Data quality; Health care; Data access; Population health; Population; Medicine; Environmental health; Political science; Computer science; Geography; Database; Marketing","score_opus":0.38678808740187065,"score_gpt":0.48914896640411754,"score_spread":0.10236087900224689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2895262614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94883233,0.0038749864,0.011077575,0.024661843,0.0026622496,0.0004804041,0.007174484,0.000018343657,0.0012177808],"genre_scores_gemma":[0.99651575,0.00067606574,0.0008538078,0.0007504325,0.00026712628,0.0000023831349,0.0009163219,0.000006161181,0.000011965731],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983212,0.000028062823,0.0005525745,0.00046063313,0.00034010832,0.00029747255],"domain_scores_gemma":[0.99878496,0.00007505838,0.00047312534,0.00029754004,0.00021744982,0.00015186986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022983681,0.000081767364,0.00017194677,0.0002762628,0.00030987913,0.0001523332,0.0011459339,0.000028355002,0.000028455173],"category_scores_gemma":[0.0006317986,0.00008055302,0.00000970049,0.0002181536,0.00013132075,0.0013875517,0.000317018,0.0001586737,7.208651e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025535308,0.0001614839,0.7954021,0.00009012835,0.00030845273,0.000028598812,0.0013213118,0.00053885137,0.0000029955502,0.12172318,0.0011740092,0.07899354],"study_design_scores_gemma":[0.0007834499,0.00018292468,0.88088536,0.00016119327,0.000004502117,0.00005998346,0.00038168224,0.09636619,0.0000016394121,0.0040400033,0.016953085,0.00018000558],"about_ca_topic_score_codex":0.49332556,"about_ca_topic_score_gemma":0.9354373,"teacher_disagreement_score":0.44211173,"about_ca_system_score_codex":0.0021188508,"about_ca_system_score_gemma":0.004418519,"threshold_uncertainty_score":0.78382623},"labels":[],"label_agreement":null},{"id":"W2895747123","doi":"10.23889/ijpds.v3i3.433","title":"The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Promotion and Cardiovascular Prevention","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Alberta Health; University of Calgary; University of Alberta; Manitoba Health; Public Health Agency of Canada; Health PEI; Institute for Clinical Evaluative Sciences; Government of Nunavut; Government of Northwest Territories; Nova Scotia Health Authority; Government of New Brunswick; Nova Scotia Department of Health and Wellness; Veterans Affairs Canada; Government of Saskatchewan; Ministry of Health; Institut National de Santé Publique du Québec; University of Manitoba","funders":"Government of Canada; Ministry of Health, Saskatchewan; Public Health Agency; Public Health Agency of Canada","keywords":"Disease surveillance; Disease registry; Public health; Disease; Chronic disease; Population; Medicine; Agency (philosophy); Environmental health; Business; Family medicine","score_opus":0.07300541383426135,"score_gpt":0.40972543944387724,"score_spread":0.3367200256096159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2895747123","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037529364,0.0009281366,0.92024463,0.022742376,0.010881975,0.0034071018,0.0035424961,0.000085732056,0.0006381925],"genre_scores_gemma":[0.9955405,0.000070277616,0.0019399108,0.00019011313,0.0012781451,0.000033404027,0.0005411329,0.000010701917,0.0003958093],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99809134,0.00011066252,0.0003669036,0.00031193835,0.00080474094,0.00031440638],"domain_scores_gemma":[0.99597466,0.00007190333,0.00021022474,0.00045311693,0.0028716866,0.00041839373],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0069539263,0.000087092165,0.0001266282,0.00016576593,0.0017219307,0.00034650232,0.0007574745,0.000034099863,0.0000074526715],"category_scores_gemma":[0.0015184336,0.000064654414,0.0000839827,0.0002804338,0.0002087111,0.00064278545,0.00006785048,0.00009491354,0.000009262245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028850778,0.00035350164,0.15753126,0.00086521794,0.0014753491,0.000071716044,0.0013107382,0.015551737,0.0010839502,0.1991636,0.070347376,0.54936045],"study_design_scores_gemma":[0.0010648804,0.00008506674,0.11751083,0.00009965372,0.000017545684,0.00007325894,0.00004845593,0.84007543,0.000008322892,0.0005635703,0.04035642,0.000096547024],"about_ca_topic_score_codex":0.0013280873,"about_ca_topic_score_gemma":0.0693498,"teacher_disagreement_score":0.95801115,"about_ca_system_score_codex":0.0012863984,"about_ca_system_score_gemma":0.0037940037,"threshold_uncertainty_score":0.9995777},"labels":[],"label_agreement":null},{"id":"W2899558153","doi":"10.23889/ijpds.v3i4.867","title":"Multi-province epidemiological research using administrative data in Canada: Challenges and opportunities","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Women's College Hospital; Centre for Addiction and Mental Health; University of Calgary; Simon Fraser University","funders":"","keywords":"Context (archaeology); Work (physics); Data collection; Health care; Business; Data access; Geography; Computer science; Political science; Database; Engineering","score_opus":0.9187614654524571,"score_gpt":0.6960131716848887,"score_spread":0.22274829376756833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899558153","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9120114,0.00072080607,0.00272702,0.073766366,0.007687644,0.0008242192,0.0015215949,0.000015151788,0.0007258044],"genre_scores_gemma":[0.98394555,0.0014029454,0.011154997,0.0013428032,0.0016561421,0.000009557034,0.0003452612,0.0000069198722,0.0001358385],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972006,0.0004891317,0.00064668903,0.00042160306,0.0007115716,0.00053038105],"domain_scores_gemma":[0.9965384,0.0011692815,0.00033082042,0.00053824735,0.0011538096,0.0002694275],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.013041834,0.00007854629,0.00014408786,0.0003036153,0.0012899277,0.000059818292,0.0019923567,0.000055389773,0.000044785495],"category_scores_gemma":[0.008523111,0.00006386335,0.0000059427284,0.00013948332,0.00036504594,0.0021087374,0.0011403052,0.00044329633,0.0000023562252],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005572275,0.00039051464,0.39093962,0.00029268963,0.00008664618,0.00007006721,0.012810929,0.00008676172,0.0006883207,0.18405536,0.076115616,0.33390623],"study_design_scores_gemma":[0.0004173597,0.00006935619,0.68196887,0.00024118442,0.0000033658196,0.000060467348,0.01585561,0.20475464,0.000001692352,0.0021177202,0.094375886,0.00013387638],"about_ca_topic_score_codex":0.5898549,"about_ca_topic_score_gemma":0.83828926,"teacher_disagreement_score":0.33377236,"about_ca_system_score_codex":0.0012773213,"about_ca_system_score_gemma":0.013231453,"threshold_uncertainty_score":0.9998285},"labels":[],"label_agreement":null},{"id":"W2900552035","doi":"10.23889/ijpds.v3i5.1059","title":"Housing Affordability: Local and National Perspectives","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Index (typography); Quarter (Canadian coin); Affordable housing; American Community Survey; Demographic economics; Business; Construct (python library); Value (mathematics); Ethnic group; Actuarial science; Economics; Geography; Economic growth; Census; Political science; Statistics; Demography; Sociology; Population","score_opus":0.0894408026372858,"score_gpt":0.34091419664537254,"score_spread":0.25147339400808677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900552035","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.714421,0.00017022582,0.25568217,0.0034940445,0.005739317,0.00021144413,0.0006681592,0.000043614313,0.019570066],"genre_scores_gemma":[0.9899551,0.00007156096,0.008973518,0.00014625509,0.0007433045,0.0000015542536,0.00004618602,0.000008318812,0.00005416131],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989162,0.000005680112,0.0003848641,0.00039001173,0.00012964007,0.00017358348],"domain_scores_gemma":[0.9990193,0.000046234854,0.0002721123,0.00018280269,0.00039757756,0.00008191857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022115866,0.00007386373,0.000111939604,0.00034010655,0.00046536318,0.00053799927,0.00075757096,0.000030949304,0.00010782618],"category_scores_gemma":[0.00091726455,0.00008210657,0.000029372006,0.00013958335,0.0004452981,0.0024528678,0.0002374582,0.00007658529,0.000029806666],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012770348,0.00010696382,0.19677138,0.0000068129293,0.000062996805,0.0000011528973,0.0010334649,0.00032707548,0.00006115475,0.74418795,0.0020609163,0.055252418],"study_design_scores_gemma":[0.0009733379,0.00011152448,0.1494969,0.000029149445,0.0000062924887,0.00012241355,0.00073632784,0.4162932,0.000040602423,0.34959128,0.08219971,0.00039926465],"about_ca_topic_score_codex":0.00010934769,"about_ca_topic_score_gemma":0.000090530484,"teacher_disagreement_score":0.41596612,"about_ca_system_score_codex":0.0003230076,"about_ca_system_score_gemma":0.00008380122,"threshold_uncertainty_score":0.5187939},"labels":[],"label_agreement":null},{"id":"W2900610889","doi":"10.23889/ijpds.v3i1.451","title":"Longitudinal child data: What can be gained by linking administrative data and cohort data?","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal; Research Unit on Children's Psychosocial Maladjustment; Statistics Canada","funders":"","keywords":"Record linkage; Linkage (software); Cohort; False positive paradox; Psychological intervention; Cohort study; Longitudinal data; Population; Longitudinal study; Actuarial science; Medicine; Psychology; Environmental health; Statistics; Computer science; Business; Data mining","score_opus":0.5285046649674737,"score_gpt":0.5641351279824764,"score_spread":0.03563046301500272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900610889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6988325,0.0014722842,0.123892,0.06982984,0.030797943,0.0016107404,0.07217151,0.00015508979,0.0012380702],"genre_scores_gemma":[0.9457677,0.0009320791,0.01979171,0.000987541,0.0025695313,0.0000029461735,0.029715046,0.000012698946,0.00022071862],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9956863,0.001113077,0.00045334527,0.0011046067,0.0012775022,0.0003651826],"domain_scores_gemma":[0.99432003,0.0023449126,0.00043067258,0.0020209542,0.00063642213,0.00024701064],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["metaresearch","scholarly_communication"],"category_scores_codex":[0.04720439,0.00013658688,0.00017167912,0.00019669546,0.0023062804,0.0016760597,0.0107948175,0.00008422964,0.00009717789],"category_scores_gemma":[0.027343692,0.00012743927,0.000013183289,0.000360768,0.0015119442,0.015360701,0.0036174962,0.00026125053,0.0000039206707],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033708652,0.00030398724,0.79796076,0.0000110127385,0.0005019813,0.000060739752,0.0050583105,0.000008789206,0.00068000087,0.009414043,0.10066626,0.08196328],"study_design_scores_gemma":[0.0011362529,0.00017877265,0.48290882,0.00023581092,0.0001343504,0.00034487658,0.004005072,0.030655218,0.00013324199,0.0021853019,0.4774781,0.00060419156],"about_ca_topic_score_codex":0.0015648128,"about_ca_topic_score_gemma":0.010345206,"teacher_disagreement_score":0.37681183,"about_ca_system_score_codex":0.00010059798,"about_ca_system_score_gemma":0.0007711916,"threshold_uncertainty_score":0.9993603},"labels":[],"label_agreement":null},{"id":"W2900710720","doi":"10.23889/ijpds.v3i1.730","title":"Vasectomy reversal and prostate cancer risk: A multi-centre collaborative demonstration project of the Intentional Population Data Linkage Network","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Vasectomy; Prostate cancer; Linkage (software); Vasectomy reversal; Record linkage; Medicine; Population; Gynecology; Cancer; Family planning; Environmental health; Research methodology; Internal medicine; Genetics; Biology","score_opus":0.06235565051988018,"score_gpt":0.4160999437490778,"score_spread":0.35374429322919765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900710720","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9709432,0.0002492881,0.011140577,0.002572232,0.008141296,0.0021189407,0.0045429915,0.00004439002,0.000247073],"genre_scores_gemma":[0.98532563,0.0004961644,0.012317266,0.00008514144,0.0010621616,0.000012413118,0.00055224897,0.000009248541,0.00013969874],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99692273,0.00028355376,0.000563688,0.00052160997,0.0014095828,0.00029883528],"domain_scores_gemma":[0.9966131,0.00010281319,0.0010090778,0.0005187277,0.0016770519,0.00007923829],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0041332156,0.00012936698,0.00014084435,0.00022461539,0.0017143907,0.00048521403,0.0021665713,0.00005607826,0.000028446433],"category_scores_gemma":[0.0014709528,0.00010350794,0.00004589923,0.0010061474,0.0008812913,0.0035145665,0.00066073885,0.00018063847,0.0000012021472],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080211954,0.00006542183,0.9775677,0.000007594397,0.000075182856,6.576629e-7,0.0012444576,0.00033177945,0.000032687836,0.006885654,0.002623336,0.011085318],"study_design_scores_gemma":[0.0007307013,0.000027611864,0.9366753,0.00014978141,0.00007038398,0.0000031041475,0.0009978904,0.048482426,0.000011106463,0.0021079492,0.010591157,0.0001525673],"about_ca_topic_score_codex":0.00943963,"about_ca_topic_score_gemma":0.03967015,"teacher_disagreement_score":0.048150644,"about_ca_system_score_codex":0.00019442686,"about_ca_system_score_gemma":0.00052439835,"threshold_uncertainty_score":0.9995853},"labels":[],"label_agreement":null},{"id":"W2901139437","doi":"10.23889/ijpds.v3i3.441","title":"Expanding the impact of a longstanding Canadian cardiac registry through data linkage: challenges and opportunities","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Calgary Laboratory Services; Alberta Children's Hospital; Libin Cardiovascular Institute of Alberta; University of Calgary","funders":"","keywords":"Medicine; Cardiac catheterization; Cohort; Record linkage; Data collection; Work (physics); Disease registry; Disease; Cohort study; Coronary artery disease; Medical emergency; Intensive care medicine; Environmental health; Surgery; Cardiology; Internal medicine; Engineering; Population","score_opus":0.47406142887293296,"score_gpt":0.5621709100179619,"score_spread":0.08810948114502898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901139437","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7878951,0.011157237,0.0062240358,0.116464265,0.026876077,0.002189238,0.01971779,0.00009158282,0.0293847],"genre_scores_gemma":[0.9906835,0.0050117588,0.001191967,0.000914899,0.0014617172,0.0000043251757,0.00054519036,0.0000095977775,0.00017704585],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982893,0.00010760323,0.00047342677,0.00027889074,0.0005018629,0.00034889986],"domain_scores_gemma":[0.99751496,0.00038897622,0.00044755245,0.0007734426,0.00068645005,0.00018860122],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0036410957,0.000091466165,0.00016232909,0.00021104763,0.0016169569,0.00009354844,0.0022028985,0.000057834324,0.00007605664],"category_scores_gemma":[0.0011684753,0.00006071527,0.000032615702,0.000100279874,0.0003124647,0.0027377747,0.0007521758,0.0002614939,0.0000025815189],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039877993,0.00006145423,0.31084156,0.0002765098,0.00054299395,0.0000426977,0.024610445,0.000021566275,0.0006646647,0.09537671,0.25783676,0.30932584],"study_design_scores_gemma":[0.0010014795,0.00024149998,0.67794603,0.00066439813,0.00007571937,0.00018927171,0.013766596,0.0043446296,0.000019026429,0.012109071,0.2892452,0.00039709406],"about_ca_topic_score_codex":0.03965475,"about_ca_topic_score_gemma":0.018216196,"teacher_disagreement_score":0.36710447,"about_ca_system_score_codex":0.00061867584,"about_ca_system_score_gemma":0.0031206384,"threshold_uncertainty_score":0.9996988},"labels":[],"label_agreement":null},{"id":"W2901302597","doi":"10.23889/ijpds.v3i5.1045","title":"Administrative Data Format Standardization for Efficient Analytics","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Computer science; Standardization; Data quality; Data management; Data science; Data pre-processing; Metadata; Data governance; Data processing; Data warehouse; Database; Data mining; World Wide Web; Engineering","score_opus":0.5881116757594165,"score_gpt":0.5992713194419055,"score_spread":0.011159643682489007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901302597","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0048251413,0.00001119596,0.9750781,0.0028904085,0.0051462078,0.00044137295,0.01106358,0.000019851988,0.0005241592],"genre_scores_gemma":[0.930027,0.000015456231,0.06265778,0.0006246463,0.0012961915,0.000008096834,0.0048630815,0.000010304932,0.00049742206],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99453473,0.00006322112,0.0010145657,0.00078873575,0.003303351,0.00029538648],"domain_scores_gemma":[0.99317694,0.00062206975,0.00081450853,0.0017902819,0.0034298196,0.00016638922],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.015996872,0.00012286426,0.0001691149,0.00057239266,0.0009868543,0.0025987641,0.00973547,0.00003439567,0.00011727203],"category_scores_gemma":[0.016983759,0.00009507621,0.000052658863,0.00073065906,0.00037321102,0.0061626183,0.0019895148,0.000080061174,0.000039386956],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00095185015,0.00036887362,0.0035817006,0.0000143718335,0.00019438384,0.0000054849,0.0008959461,0.008862997,0.0002892292,0.26321554,0.43718728,0.28443232],"study_design_scores_gemma":[0.0005114861,0.00011731129,0.002886443,0.000018004417,0.000022327875,0.00001802284,0.00047328093,0.5718463,0.00010158524,0.018225687,0.405654,0.0001255464],"about_ca_topic_score_codex":0.000023259301,"about_ca_topic_score_gemma":0.00019468369,"teacher_disagreement_score":0.9252019,"about_ca_system_score_codex":0.00017288029,"about_ca_system_score_gemma":0.00037074092,"threshold_uncertainty_score":0.9984366},"labels":[],"label_agreement":null},{"id":"W2901578635","doi":"10.23889/ijpds.v3i5.1065","title":"Key Factors in the establishment of an academia-government center of public sector administrative data and policy research","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Government of New Brunswick","funders":"","keywords":"General partnership; Public sector; Public administration; Public relations; Government (linguistics); Political science; Business; Law","score_opus":0.5989404149628077,"score_gpt":0.6546144802705751,"score_spread":0.05567406530776742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901578635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9743242,0.000010452225,0.00032629722,0.020846084,0.0011906604,0.00044573823,0.0023324895,0.0000029400956,0.00052109687],"genre_scores_gemma":[0.9968443,0.000054259133,0.0008294798,0.00052902615,0.0011459417,0.0000106414345,0.0005355487,0.0000049128416,0.000045883633],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9963855,0.0004942072,0.0007211733,0.0002911536,0.0017105883,0.0003973826],"domain_scores_gemma":[0.99684674,0.00070429663,0.0005333521,0.00067223137,0.0010626247,0.00018073659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013445974,0.00006893728,0.00011412554,0.0004057844,0.00066889456,0.000104452025,0.0031245456,0.000081370934,0.000059600796],"category_scores_gemma":[0.006821736,0.000046554494,0.000010399376,0.00060048286,0.00040994067,0.0031352974,0.0008427004,0.0005264355,0.0000010613397],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013671049,0.0004574375,0.87277937,0.000069159156,0.000027046415,5.13578e-7,0.028975936,0.0000031991126,0.0006625209,0.064158745,0.018543566,0.014185824],"study_design_scores_gemma":[0.00055630447,0.00022937632,0.8863096,0.00011909231,0.0000030765314,0.000008211396,0.020871261,0.0052360436,0.00006224924,0.002329585,0.084208116,0.00006706159],"about_ca_topic_score_codex":0.0034241902,"about_ca_topic_score_gemma":0.0017981076,"teacher_disagreement_score":0.06566455,"about_ca_system_score_codex":0.0004408888,"about_ca_system_score_gemma":0.0018581942,"threshold_uncertainty_score":0.8166748},"labels":[],"label_agreement":null},{"id":"W2901669259","doi":"10.23889/ijpds.v3i3.440","title":"Lessons Learned: It Takes a Village to Understand Inter-Sectoral Care Using Administrative Data across Jurisdictions","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"CancerCare Manitoba; Nova Scotia Health Authority; University Health Network; University of Toronto; CARE Canada; Dalhousie University; University of Manitoba; BC Cancer Agency; Cancer Care Ontario; Queen's University","funders":"","keywords":"Documentation; Health care; Comparability; Population; Breast cancer; Cancer registry; Data dictionary; Medicine; Cancer; Business; Family medicine; Geography; Computer science; Political science; Environmental health; World Wide Web","score_opus":0.6811977416736362,"score_gpt":0.6086569179741187,"score_spread":0.07254082369951753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901669259","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.686147,0.00010503842,0.28545663,0.014732911,0.0050726063,0.0005672975,0.0067752413,0.000055544308,0.0010877739],"genre_scores_gemma":[0.9768488,0.000010996769,0.020166775,0.00085035415,0.001236322,0.0000016857134,0.0007750768,0.00001143976,0.00009856095],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975797,0.000022707203,0.00040695918,0.00059293595,0.0010607739,0.0003369524],"domain_scores_gemma":[0.99732697,0.000049411767,0.00022490279,0.0007489158,0.0013694823,0.00028029125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009807623,0.00013083241,0.00015899226,0.00022204341,0.00089076237,0.00064325,0.002023979,0.000046008096,0.00009135032],"category_scores_gemma":[0.0012085607,0.000116994415,0.000043842752,0.0004416898,0.00030437374,0.002824186,0.0006401535,0.00018381863,0.000013463879],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00935782,0.0008074059,0.3786651,0.0001669828,0.001412282,0.0006208767,0.08360801,0.0040219557,0.060583476,0.018660074,0.109076545,0.3330195],"study_design_scores_gemma":[0.0069037937,0.0038736337,0.21411487,0.003320917,0.0005154594,0.005464882,0.14867517,0.24862815,0.0035539502,0.002710527,0.3604677,0.0017709126],"about_ca_topic_score_codex":0.0006729342,"about_ca_topic_score_gemma":0.0034223946,"teacher_disagreement_score":0.33124858,"about_ca_system_score_codex":0.00060748635,"about_ca_system_score_gemma":0.00067018985,"threshold_uncertainty_score":0.6851114},"labels":[],"label_agreement":null},{"id":"W2901960400","doi":"10.23889/ijpds.v3i5.1075","title":"Evaluating the impact of workers' compensation policy in Australia using insurance claims data and comparative quasi-experimental methods","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Legislature; Workers' compensation; Disability insurance; Work (physics); Business; Quarter (Canadian coin); Unintended consequences; Actuarial science; Duration (music); Demographic economics; Compensation (psychology); Economics; Geography; Political science; Psychology; Engineering; Law","score_opus":0.6864750878037543,"score_gpt":0.6293747520779046,"score_spread":0.057100335725849716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901960400","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9673449,0.00008434561,0.030237243,0.00074528664,0.0005935206,0.00022493851,0.0006873635,0.000002801971,0.00007962401],"genre_scores_gemma":[0.9657201,0.000011480553,0.033819996,0.00005330278,0.00027900658,0.0000021680453,0.000095057105,0.0000032567118,0.000015643664],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871093,0.000068725676,0.0006093133,0.00030244823,0.00013912957,0.00016944428],"domain_scores_gemma":[0.99870026,0.00011193894,0.0005910035,0.00040270263,0.00014174326,0.0000523284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048584887,0.000075128584,0.00015985167,0.00039175677,0.00023901343,0.00018097022,0.0012715255,0.000022625058,0.000024280665],"category_scores_gemma":[0.0006256057,0.00006316464,0.000023095006,0.00037436563,0.00022571997,0.0017657403,0.0004505087,0.00009378848,0.0000027326676],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027273878,0.0003162732,0.74675065,0.000015774269,0.0001309547,7.518134e-7,0.0041369596,0.0075482083,0.0020629452,0.22140476,0.00034018134,0.01701978],"study_design_scores_gemma":[0.0003387802,0.00015562383,0.40920588,0.00003152038,0.0000016791215,0.000011063683,0.00018518002,0.5796746,0.00006096946,0.010007097,0.0002599847,0.000067641646],"about_ca_topic_score_codex":0.02233377,"about_ca_topic_score_gemma":0.00030023287,"teacher_disagreement_score":0.5721264,"about_ca_system_score_codex":0.00030307376,"about_ca_system_score_gemma":0.00011139197,"threshold_uncertainty_score":0.9841766},"labels":[],"label_agreement":null},{"id":"W2906567312","doi":"10.23889/ijpds.v4i1.586","title":"Consensus Statement on Public Involvement and Engagement with Data-Intensive Health Research","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Mental Health and Patient Involvement","field":"Health Professions","cited_by":103,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of British Columbia","funders":"Economic and Social Research Council; Engineering and Physical Sciences Research Council; Wellcome Trust; Academy of Medical Sciences; British Heart Foundation; Cancer Research UK; Medical Research Council; National Institute for Social Care and Health Research","keywords":"Premise; Key (lock); Public relations; Public engagement; Statement (logic); Public health; Field (mathematics); Problem statement; Political science; Knowledge management; Medicine; Management science; Computer science; Nursing; Engineering; Law; Computer security; Epistemology","score_opus":0.8330799193448962,"score_gpt":0.630687672687338,"score_spread":0.20239224665755817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2906567312","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.947217,0.00013597739,0.0013704941,0.036547933,0.0067739575,0.0044253105,0.0027672073,0.0000340177,0.00072813354],"genre_scores_gemma":[0.9790142,0.0002261673,0.0051336847,0.008750546,0.00035132084,0.000060424267,0.005889557,0.00001764255,0.0005564602],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9943918,0.0005637576,0.0009421648,0.0007421404,0.0025760136,0.000784096],"domain_scores_gemma":[0.9947861,0.00074322213,0.00066250435,0.0009965504,0.0023212822,0.000490381],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.018071627,0.00014019724,0.00018931886,0.00057291664,0.0022105793,0.00018278879,0.0018483528,0.00003500601,0.00018373983],"category_scores_gemma":[0.00069927896,0.00010358492,0.000012512099,0.0003028745,0.00017518426,0.0010802964,0.0014739849,0.000655776,0.000091616064],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017398399,0.0005867072,0.7395835,0.0006816296,0.00018369847,0.000015962269,0.004541279,0.0001962727,0.0001450765,0.068191126,0.13458401,0.04955089],"study_design_scores_gemma":[0.0074755023,0.0040699593,0.109026864,0.002842054,0.000016502398,0.000029717214,0.030141192,0.03916498,0.000028097496,0.0031234813,0.8035967,0.00048495946],"about_ca_topic_score_codex":0.00086744176,"about_ca_topic_score_gemma":0.00081337115,"teacher_disagreement_score":0.66901267,"about_ca_system_score_codex":0.0012070491,"about_ca_system_score_gemma":0.0017794605,"threshold_uncertainty_score":0.9990884},"labels":[],"label_agreement":null},{"id":"W2910640220","doi":"10.23889/ijpds.v4i1.453","title":"Risk factors for hospitalizations associated with depression among women during the years around a birth: a retrospective cohort study","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal Mental Health During Pregnancy and Postpartum","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BC Children's Hospital","funders":"","keywords":"Decile; Medicine; Depression (economics); Retrospective cohort study; Demography; Cohort; Medical prescription; Pregnancy; Cohort study; Odds ratio; Pediatrics; Psychiatry; Internal medicine","score_opus":0.020769695006731738,"score_gpt":0.3379347034551775,"score_spread":0.31716500844844575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910640220","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960694,0.000009581694,0.00045138426,0.000055573,0.0011930938,0.0017121705,0.00046398278,0.000023227758,0.00002158724],"genre_scores_gemma":[0.9988887,0.00001192417,0.0001181453,0.000028565208,0.00012505909,0.00007217875,0.00019690653,0.000014449264,0.0005441188],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99817514,0.000035988312,0.0003066769,0.00033677704,0.0008974695,0.00024793975],"domain_scores_gemma":[0.99856883,0.00012689034,0.00043986193,0.00032994035,0.0004152939,0.00011917573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011664411,0.000101801576,0.00015703958,0.00017150938,0.0005363632,0.00020785106,0.0005955493,0.000028622484,0.00003500935],"category_scores_gemma":[0.0007722463,0.000065486965,0.000033783104,0.00021866265,0.00007409312,0.0010424618,0.00012866693,0.00016426534,0.0000019974443],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026714895,0.00012662933,0.99848044,0.000016436295,0.000096380776,0.0000028166385,0.0006434294,0.00026004223,0.000019014813,0.000038669357,0.000008437084,0.00004056224],"study_design_scores_gemma":[0.00145429,0.00035989913,0.99257934,0.00039172333,0.00003645109,0.000021378732,0.0005405953,0.004320888,0.000031632633,0.00014830967,0.000031747677,0.00008371994],"about_ca_topic_score_codex":0.0002720641,"about_ca_topic_score_gemma":0.000099821045,"teacher_disagreement_score":0.0059010684,"about_ca_system_score_codex":0.0006191145,"about_ca_system_score_gemma":0.0000943143,"threshold_uncertainty_score":0.41253266},"labels":[],"label_agreement":null},{"id":"W2911764939","doi":"10.23889/ijpds.v4i1.465","title":"The Experience of Establishing Data Sharing &amp; Linkage Platforms for Administrative, Research and Community-Service Data","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; Alberta Health; Alberta Health Services","funders":"","keywords":"Thematic analysis; Context (archaeology); Data sharing; Qualitative property; Knowledge management; Linked data; Stakeholder; Open data; Sustainability; Flexibility (engineering); Biobank; Data science; Business; Public relations; Computer science; World Wide Web; Qualitative research; Political science; Sociology; Semantic Web; Geography; Management","score_opus":0.5804475203613262,"score_gpt":0.5736864749201441,"score_spread":0.006761045441182056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911764939","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98038954,0.00006895369,0.011039805,0.0024702798,0.0011453344,0.0004637367,0.0038361372,0.00001205568,0.0005741638],"genre_scores_gemma":[0.9852737,0.000199879,0.010485619,0.000057839596,0.00029566264,0.0000048903808,0.0034154826,0.0000070096585,0.00025987276],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99707437,0.00011393334,0.0004764499,0.0005047478,0.0014920101,0.00033846646],"domain_scores_gemma":[0.9933844,0.002730469,0.00038172604,0.002382185,0.000993549,0.00012762536],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.025843335,0.00007611832,0.00012245704,0.00020529624,0.0043819034,0.0025113043,0.01957886,0.000029472532,0.000018998],"category_scores_gemma":[0.011403792,0.00005667114,0.000016554375,0.0005437088,0.0005824956,0.011781778,0.0070644687,0.00040941796,0.0000021709775],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057924574,0.00059840095,0.3690747,0.00015167378,0.0003126363,0.0000030025565,0.06509948,0.0003562375,0.007877891,0.36087677,0.009748087,0.18532185],"study_design_scores_gemma":[0.0011489281,0.00016971958,0.056495957,0.00059861416,0.00004640322,0.000028706967,0.08712105,0.30773753,0.00011141963,0.05838294,0.48765635,0.0005023781],"about_ca_topic_score_codex":0.004843596,"about_ca_topic_score_gemma":0.022570126,"teacher_disagreement_score":0.47790825,"about_ca_system_score_codex":0.00006186542,"about_ca_system_score_gemma":0.00035638353,"threshold_uncertainty_score":0.9985242},"labels":[],"label_agreement":null},{"id":"W2929814923","doi":"10.23889/ijpds.v4i1.584","title":"Using Canadian administrative health data to measure the health of caregivers of children with and without health problems: A demonstration of feasibility.","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Childhood Cancer Survivors' Quality of Life","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; Ottawa Hospital; University of Manitoba; Statistics Canada; McGill University; University of British Columbia","funders":"","keywords":"Categorical variable; Medicine; Population; Medical diagnosis; Population health; Mood; Anxiety; Psychology; Environmental health; Gerontology; Psychiatry","score_opus":0.26187777080865593,"score_gpt":0.4701660191604838,"score_spread":0.20828824835182785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2929814923","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9653806,0.00025134796,0.0058087986,0.023546856,0.00026828266,0.0017734146,0.0029504034,0.000004264606,0.000016024824],"genre_scores_gemma":[0.98640114,0.000031548076,0.012354282,0.0006407824,0.00005617632,0.0000011490495,0.00050380145,0.0000069676553,0.000004160029],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974556,0.00011565356,0.0007378684,0.00036366543,0.0011248484,0.00020233862],"domain_scores_gemma":[0.99705213,0.000050204013,0.0011755229,0.0006781027,0.00071105105,0.00033297684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004330964,0.0000947766,0.00032702755,0.00027341748,0.00019078632,0.000040437946,0.00090403686,0.000019539088,0.0000049954656],"category_scores_gemma":[0.00038551824,0.000069650574,0.000021696673,0.0003341293,0.00021146338,0.0008064057,0.0001343511,0.00013003536,1.1692084e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027651296,0.00006687505,0.9908562,0.00013718738,0.00009261435,1.0007328e-7,0.0033678873,0.000440479,0.00012521466,0.0006598033,0.00023037144,0.0037467822],"study_design_scores_gemma":[0.0014549423,0.0014344993,0.9877307,0.0013908438,0.000020566611,0.00021803266,0.0024226313,0.004991703,0.00005008067,0.00007155861,0.00011981486,0.00009466057],"about_ca_topic_score_codex":0.15958735,"about_ca_topic_score_gemma":0.2404812,"teacher_disagreement_score":0.080893844,"about_ca_system_score_codex":0.00044433778,"about_ca_system_score_gemma":0.008176321,"threshold_uncertainty_score":0.9974464},"labels":[],"label_agreement":null},{"id":"W2944477024","doi":"10.23889/ijpds.v4i1.1103","title":"Sharing linked data sets for research: results from a deliberative public engagement event in British Columbia, Canada","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"BC Centre for Disease Control; University of Guelph; Canadian Centre for Applied Research in Cancer Control; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Deliberation; Data sharing; Public relations; Voting; Event (particle physics); Public engagement; Internet privacy; Data governance; Process (computing); Political science; Data quality; Computer science; Business; Medicine; Law","score_opus":0.34260095056867745,"score_gpt":0.48586712523563313,"score_spread":0.14326617466695568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944477024","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96963924,0.00003577728,0.0027164014,0.006096255,0.002390051,0.0007548188,0.017962351,0.000012034375,0.00039305],"genre_scores_gemma":[0.98437697,0.00006271478,0.0048763207,0.00015828451,0.00042356932,0.000011713827,0.009412872,0.000007201363,0.0006703498],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99587995,0.0001946288,0.0006156769,0.00077025895,0.0020784596,0.00046100785],"domain_scores_gemma":[0.99708414,0.0008556997,0.0002992988,0.00072102423,0.0008527367,0.0001870905],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0149521865,0.000060130405,0.00013588423,0.00021534774,0.0014104978,0.0041331556,0.006027652,0.000027797274,0.000117662865],"category_scores_gemma":[0.01036861,0.00008295157,0.000028609229,0.0005041231,0.00013053793,0.0049484875,0.00172543,0.00027048457,0.0000029394928],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013561173,0.00031707264,0.5763435,0.000013729026,0.00022333098,0.000044399156,0.0043316786,0.0017256923,0.0003234849,0.006490687,0.10195436,0.30809647],"study_design_scores_gemma":[0.0016098457,0.000034654382,0.35957658,0.00029488243,0.000013830771,0.0000048168267,0.0049066916,0.28818807,0.0000021231585,0.009931566,0.33515024,0.00028671083],"about_ca_topic_score_codex":0.9358504,"about_ca_topic_score_gemma":0.9970747,"teacher_disagreement_score":0.30780974,"about_ca_system_score_codex":0.0007396125,"about_ca_system_score_gemma":0.0020778982,"threshold_uncertainty_score":0.99988955},"labels":[],"label_agreement":null},{"id":"W2965977938","doi":"10.23889/ijpds.v4i1.1106","title":"Notches on the dial: a call to action to develop plain language communication with the public about users and uses of health data","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Focus Groups and Qualitative Methods","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of British Columbia; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Call to action; Action (physics); Dial; Computer science; Plain language; Psychology; Linguistics; Engineering; Business; Advertising","score_opus":0.3586367229366417,"score_gpt":0.5420807147469173,"score_spread":0.1834439918102756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965977938","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7973341,0.000090485075,0.03351772,0.16697954,0.00066669297,0.00075266365,0.00039983663,0.000013186213,0.00024578007],"genre_scores_gemma":[0.977978,0.00005527664,0.020210706,0.0014248346,0.000083297644,0.0000071296804,0.000109017135,0.0000050428957,0.00012671262],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99801445,0.0005106765,0.0002474895,0.00022447926,0.000843425,0.00015947093],"domain_scores_gemma":[0.99751437,0.00101776,0.00030179086,0.0005628866,0.00051485596,0.000088351335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012879281,0.000060097824,0.00009044789,0.00014511112,0.00083208777,0.0004207846,0.002607404,0.000015712638,0.000011430781],"category_scores_gemma":[0.0041158623,0.00003379396,0.00000900626,0.00056483893,0.00022812867,0.0014363752,0.00042521502,0.00010748853,0.0000034850943],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028505796,0.00010805394,0.035890047,0.000015920898,0.00008058005,5.7430105e-7,0.07106634,0.0003146612,0.0010106278,0.36544478,0.017254334,0.508529],"study_design_scores_gemma":[0.0007503546,0.00043455046,0.40644994,0.0003795767,0.000018227514,0.000017887243,0.076069295,0.006533591,0.00021041319,0.0021015187,0.50665283,0.00038177782],"about_ca_topic_score_codex":0.003281179,"about_ca_topic_score_gemma":0.010128062,"teacher_disagreement_score":0.50814724,"about_ca_system_score_codex":0.00013309137,"about_ca_system_score_gemma":0.00035676008,"threshold_uncertainty_score":0.63998306},"labels":[],"label_agreement":null},{"id":"W2966802368","doi":"10.23889/ijpds.v4i1.1102","title":"Population-based study of the association between food insecurity and preventable hospitalization among persons with diabetes using linked survey and administrative data","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick","funders":"Canadian Institutes of Health Research; Diabetes Canada; Fondation de la recherche en santé du Nouveau-Brunswick; Heart and Stroke Foundation of Canada; Diabetes Action Research and Education Foundation","keywords":"Medicine; Socioeconomic status; Environmental health; Diabetes mellitus; Logistic regression; Population; Odds; Odds ratio; Demography; Gerontology","score_opus":0.29088395773278125,"score_gpt":0.4904731741066459,"score_spread":0.19958921637386468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2966802368","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938278,0.00001725701,0.00030909738,0.0002889186,0.0008580716,0.00149958,0.0031773334,0.000011754013,0.000010158003],"genre_scores_gemma":[0.99733764,0.0000030893245,0.0007927814,0.00005662644,0.00014002218,0.000009991942,0.0016243071,0.000011133793,0.000024381721],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972217,0.00045706503,0.0006580358,0.00044286964,0.0009590153,0.0002612983],"domain_scores_gemma":[0.9964331,0.00079230464,0.0012976746,0.0005555742,0.00081239024,0.000108993634],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0035135597,0.00012534516,0.00023286948,0.00021194234,0.0014176391,0.00013320752,0.0010593063,0.0000940469,0.000016953007],"category_scores_gemma":[0.0017291276,0.00009767565,0.00001602408,0.00040830366,0.00007672675,0.0024960698,0.00056460535,0.0003252382,4.845643e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003586758,0.00007707339,0.9981958,0.00003702185,0.00006392094,5.5842406e-8,0.0009207136,0.00031999336,0.0000075909497,0.0002474475,0.00003160416,0.00006290251],"study_design_scores_gemma":[0.001108698,0.0002387963,0.953422,0.00017659391,0.00006445258,2.834329e-7,0.0010732469,0.04353997,0.0000017082489,0.00023242831,0.000036801437,0.00010502322],"about_ca_topic_score_codex":0.0033770218,"about_ca_topic_score_gemma":0.012758679,"teacher_disagreement_score":0.04477381,"about_ca_system_score_codex":0.00030390322,"about_ca_system_score_gemma":0.00046007812,"threshold_uncertainty_score":0.9998824},"labels":[],"label_agreement":null},{"id":"W2989595036","doi":"10.23889/ijpds.v4i3.1325","title":"Data intensive science and the public good: Results of public deliberations in British Columbia, Canada","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Deliberation; Data sharing; Context (archaeology); Public relations; Political science; Data governance; Public engagement; Internet privacy; Business; Data quality; Computer science; Medicine; Geography; Politics; Law","score_opus":0.43705365492508774,"score_gpt":0.5353688602701577,"score_spread":0.09831520534506999,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989595036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.923414,0.00009104228,0.00044548814,0.07030882,0.0021018006,0.00066577655,0.0024051508,0.000006265967,0.0005616726],"genre_scores_gemma":[0.9957134,0.00017973478,0.0018151542,0.0011337387,0.00011305136,0.0000037243224,0.000519113,0.0000054383927,0.00051664293],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99459994,0.000067999616,0.0007863274,0.0005671507,0.00368233,0.00029627493],"domain_scores_gemma":[0.98326826,0.0032610307,0.00042749272,0.0013414916,0.011432109,0.00026961786],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.024927147,0.000051980907,0.00017081309,0.00025018895,0.0003900626,0.0015245249,0.004199166,0.000046266807,0.000034899946],"category_scores_gemma":[0.1914015,0.00005208445,0.0000165548,0.0009581195,0.0016765901,0.0033287317,0.0020394854,0.0006364998,0.000001259215],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032218784,0.00020351104,0.86935335,0.00005300067,0.00008657542,0.000047170422,0.00017301425,0.00005052515,0.000823325,0.04767076,0.019412788,0.061803784],"study_design_scores_gemma":[0.005814961,0.00010262763,0.84584403,0.0003571061,0.000015749838,0.00064901775,0.0009257532,0.115380146,0.000016201622,0.010541563,0.020208634,0.00014420922],"about_ca_topic_score_codex":0.39584005,"about_ca_topic_score_gemma":0.9680788,"teacher_disagreement_score":0.5722388,"about_ca_system_score_codex":0.00042542364,"about_ca_system_score_gemma":0.010122893,"threshold_uncertainty_score":0.999512},"labels":[],"label_agreement":null},{"id":"W2989713707","doi":"10.23889/ijpds.v4i3.1189","title":"Health conditions, disability and economic inactivity in Northern Ireland. An administrative data study.","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Economic and Social Research Council","keywords":"Census; Receipt; Population; Mental health; Demography; Valuation (finance); Geography; Medicine; Gerontology; Business; Environmental health; Finance","score_opus":0.22629144749789945,"score_gpt":0.5623308666022272,"score_spread":0.3360394191043278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989713707","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9897285,0.000017954948,0.00008915008,0.0058273305,0.0016305706,0.0008489561,0.0017555812,0.000012671508,0.00008930013],"genre_scores_gemma":[0.9979948,0.00003413875,0.00016116982,0.0001426474,0.00022582959,0.000015152791,0.0013667463,0.0000058355695,0.000053688753],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99818516,0.00021622654,0.00053075363,0.0004959339,0.0003459144,0.00022601716],"domain_scores_gemma":[0.9984618,0.00029331812,0.000387482,0.0006009032,0.0001465889,0.00010990741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028204198,0.00009104571,0.00018702075,0.0001125753,0.0007969782,0.00008552409,0.0012196164,0.000026000993,0.000058786965],"category_scores_gemma":[0.0003686457,0.00007762153,0.000010497935,0.00008471801,0.0001424279,0.0038129808,0.00077300175,0.00023905565,0.000013731034],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006579323,0.0001451489,0.9951425,0.0000067206965,0.000014746179,5.8450615e-7,0.0006530357,0.000019902089,0.0000039839656,0.0009945332,0.00028550386,0.0026675523],"study_design_scores_gemma":[0.00086622726,0.00016430973,0.9895636,0.000041147145,0.0000040912087,0.0000041529265,0.0029705178,0.003881844,2.029086e-7,0.0011832535,0.0012412315,0.00007943632],"about_ca_topic_score_codex":0.0050200396,"about_ca_topic_score_gemma":0.11907098,"teacher_disagreement_score":0.11405093,"about_ca_system_score_codex":0.0005389361,"about_ca_system_score_gemma":0.00046510473,"threshold_uncertainty_score":0.8970037},"labels":[],"label_agreement":null},{"id":"W2989842504","doi":"10.23889/ijpds.v4i3.1311","title":"Alberta's Data and Analytic Strategy: Leveraging Linked Data to Drive Innovation","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health","funders":"","keywords":"Business; Data access; Stakeholder; Data quality; Raw data; Health data; Health care; Public relations; Marketing; Computer science; Database; Economics; Political science; Economic growth","score_opus":0.6701320095536344,"score_gpt":0.6303662328664161,"score_spread":0.03976577668721826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989842504","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9380214,0.000042991964,0.023299973,0.032688048,0.0026150323,0.0009064171,0.0014584401,0.00002495204,0.00094272307],"genre_scores_gemma":[0.9766879,0.00007213073,0.014611373,0.0011636686,0.0004532162,0.0000016262892,0.005656995,0.000012947904,0.0013401147],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99598294,0.000030440699,0.00069306296,0.00093684037,0.002094984,0.0002617529],"domain_scores_gemma":[0.993669,0.0013342144,0.0002936349,0.0025051876,0.0019706965,0.00022726825],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.009396904,0.00010509708,0.00017728335,0.0006352119,0.00021943753,0.000621287,0.005112977,0.00008172908,0.00010776733],"category_scores_gemma":[0.02782091,0.000091251546,0.0000137921625,0.0008112308,0.00015260564,0.0038794994,0.0040169186,0.000697801,0.00004289678],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010369226,0.00037756772,0.69173336,0.00015992307,0.0003387698,0.000048976504,0.0004835467,0.0014967333,0.015830008,0.08410602,0.019638551,0.18474965],"study_design_scores_gemma":[0.0016638839,0.00022186757,0.27185434,0.00047018603,0.00005204599,0.00027548673,0.00023560555,0.6859892,0.000044962908,0.015957115,0.023001075,0.00023422178],"about_ca_topic_score_codex":0.00060463866,"about_ca_topic_score_gemma":0.0006123913,"teacher_disagreement_score":0.68449247,"about_ca_system_score_codex":0.00015413658,"about_ca_system_score_gemma":0.0009088372,"threshold_uncertainty_score":0.9803682},"labels":[],"label_agreement":null},{"id":"W2989899073","doi":"10.23889/ijpds.v4i2.1132","title":"Achieving quality primary care data: a description of the Canadian Primary Care Sentinel Surveillance Network data capture, extraction, and processing in Alberta","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Health Sciences Centre; University of Alberta; University of Calgary","funders":"","keywords":"Data extraction; Documentation; Raw data; Data quality; Computer science; Data collection; Automatic identification and data capture; Data science; Data mining; Medicine; Database; MEDLINE; Engineering; Operations management","score_opus":0.2909527357169971,"score_gpt":0.4888541672552275,"score_spread":0.19790143153823042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989899073","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97294676,0.0011072617,0.0037658683,0.00558381,0.008795547,0.0016431427,0.0027194764,0.000023509097,0.0034145988],"genre_scores_gemma":[0.9870045,0.00006804211,0.0019325257,0.00097496493,0.00043242166,0.000004963855,0.009477524,0.000007797293,0.000097224874],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99718076,0.00021634286,0.0009427501,0.00039826173,0.0009146724,0.0003472025],"domain_scores_gemma":[0.99689054,0.0002510842,0.00090240367,0.00096240366,0.0008320537,0.00016148436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051930724,0.00009837972,0.00018374529,0.00019106007,0.0012482796,0.00014333239,0.0023446148,0.000099054545,0.000012678663],"category_scores_gemma":[0.0016319242,0.00007640447,0.000013870121,0.000338528,0.00009183306,0.004281268,0.0009937094,0.0005648831,0.0000029104608],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043738957,0.000007633464,0.988712,0.0005730494,0.0000034712066,2.5143314e-7,0.001321269,0.0002723762,0.000028227036,0.00030008436,0.0010305581,0.007707313],"study_design_scores_gemma":[0.00045687234,0.0000060617167,0.96561766,0.0008326602,0.000006027236,0.000009702547,0.0010349685,0.020185182,1.8085034e-7,0.00007231588,0.011694123,0.00008427548],"about_ca_topic_score_codex":0.09855752,"about_ca_topic_score_gemma":0.43464667,"teacher_disagreement_score":0.33608913,"about_ca_system_score_codex":0.0008854155,"about_ca_system_score_gemma":0.0031622704,"threshold_uncertainty_score":0.9600884},"labels":[],"label_agreement":null},{"id":"W2990294467","doi":"10.23889/ijpds.v4i3.1326","title":"Building a Canadian Data Platform under the Strategy for Patient-Oriented Research","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Data sharing; Data access; Data governance; Documentation; Data management; Data science; Open data; Business; Corporate governance; Computer science; Process management; Knowledge management; Data quality; World Wide Web; Medicine; Data mining; Marketing","score_opus":0.6760014701077551,"score_gpt":0.6348692432970178,"score_spread":0.04113222681073736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990294467","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8894012,0.000052768693,0.058414377,0.0391523,0.006716378,0.002671084,0.0032390954,0.000023305349,0.00032950923],"genre_scores_gemma":[0.97742546,0.000014312349,0.017031724,0.001252093,0.0006412111,0.000011384231,0.0034902156,0.000013307356,0.000120297096],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968745,0.000039850976,0.00072697987,0.0004688472,0.0015097477,0.00038004722],"domain_scores_gemma":[0.9951173,0.0011822031,0.00031451668,0.0009925173,0.0021479724,0.00024550373],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.007987182,0.00008311011,0.00010772564,0.00042637045,0.00062217924,0.0004329648,0.002133007,0.00004101787,0.00013120902],"category_scores_gemma":[0.008499868,0.000059910202,0.00003497571,0.00034207542,0.000120608864,0.0035577267,0.0005541549,0.0003310118,0.000018923729],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026642089,0.00041790225,0.090365216,0.00006172744,0.00047879928,0.000025925254,0.00048274358,0.007190794,0.0072955675,0.2075687,0.12921764,0.55423075],"study_design_scores_gemma":[0.0032718712,0.0005700148,0.06917347,0.00015022283,0.000080064434,0.00038688086,0.0031875763,0.5086602,0.0001076547,0.013609092,0.40058205,0.00022091685],"about_ca_topic_score_codex":0.019036483,"about_ca_topic_score_gemma":0.023273258,"teacher_disagreement_score":0.55400985,"about_ca_system_score_codex":0.0005193132,"about_ca_system_score_gemma":0.0017428639,"threshold_uncertainty_score":0.99985194},"labels":[],"label_agreement":null},{"id":"W2990325812","doi":"10.23889/ijpds.v4i3.1209","title":"Linked Administrative Data at Statistics Canada – new data resources for horizontal research","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Record linkage; Linkage (software); Immigration; Analytics; Data science; Business; Public relations; Geography; Database; Political science; Sociology; Computer science; Law","score_opus":0.6937162468840304,"score_gpt":0.6065499564550645,"score_spread":0.08716629042896595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990325812","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08807018,0.00017229922,0.38939643,0.028132485,0.024065033,0.0030987419,0.46543375,0.000045530047,0.0015855592],"genre_scores_gemma":[0.69938976,0.00008885317,0.15998206,0.0012670959,0.0032224953,0.00001605814,0.11141714,0.00004224172,0.024574336],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.990311,0.0001801672,0.0010441005,0.001439019,0.006553828,0.00047188424],"domain_scores_gemma":[0.9891706,0.0033471875,0.0006894989,0.004446929,0.0019908103,0.00035497095],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.022138195,0.0001437089,0.0002199523,0.00044249295,0.00093780115,0.0025062284,0.027101718,0.000041828276,0.00037011824],"category_scores_gemma":[0.026722569,0.00011654571,0.000021278174,0.000679787,0.00023851646,0.007172492,0.010801751,0.00024299808,0.00006374328],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002495709,0.000038872942,0.003403589,0.0000050284775,0.000041472766,0.00000787681,0.00009972018,0.000095551804,0.000089917776,0.017168676,0.93159866,0.04720106],"study_design_scores_gemma":[0.0006304268,0.00011025801,0.016493328,0.000026646954,0.000012572468,0.00002736153,0.0008409765,0.08805827,0.000011948782,0.013071982,0.88055587,0.00016035834],"about_ca_topic_score_codex":0.073937654,"about_ca_topic_score_gemma":0.48490328,"teacher_disagreement_score":0.61131954,"about_ca_system_score_codex":0.00047698582,"about_ca_system_score_gemma":0.0027558606,"threshold_uncertainty_score":0.99852926},"labels":[],"label_agreement":null},{"id":"W2990677729","doi":"10.23889/ijpds.v4i3.1208","title":"Building a research partnership between computer scientists and health service researchers for access and analysis of population-level health datasets: what are we learning?","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Vector Institute","funders":"","keywords":"General partnership; Timeline; Population; Computer science; Population health; Data science; Data access; Knowledge management; Political science; Medicine; Environmental health; Database","score_opus":0.8182501156319368,"score_gpt":0.6768587331069943,"score_spread":0.14139138252494254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990677729","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91494805,0.00047769555,0.021541469,0.060058374,0.00089810824,0.0011323066,0.0009291152,0.000012922086,0.0000019525307],"genre_scores_gemma":[0.98086154,0.00062480295,0.0131039275,0.0006332404,0.00034099654,0.000010014,0.004385836,0.000010331605,0.000029322826],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968536,0.00015130034,0.0007284609,0.00056356745,0.0012967548,0.00040629986],"domain_scores_gemma":[0.9963295,0.0006964754,0.0005992615,0.00036863415,0.0016297577,0.0003763768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011252185,0.000095042924,0.00032168074,0.0015553028,0.00075154315,0.0008484006,0.00081212353,0.00004740182,0.000013643802],"category_scores_gemma":[0.0010482585,0.000087469016,0.000038691105,0.0015918951,0.0001613336,0.003318943,0.00040154642,0.00029351807,9.185809e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000104001185,0.000041961615,0.83684844,0.0002205886,0.0001027307,3.4171939e-7,0.0006834273,0.0009191921,0.00002165884,0.0011252671,0.0010956451,0.15883674],"study_design_scores_gemma":[0.00019946544,0.00025499763,0.8115742,0.00070441747,0.000041333977,0.000014832112,0.0011102462,0.18068367,0.000026556634,0.0019700122,0.0033311038,0.00008915707],"about_ca_topic_score_codex":0.0043841526,"about_ca_topic_score_gemma":0.0011953592,"teacher_disagreement_score":0.17976448,"about_ca_system_score_codex":0.00039970136,"about_ca_system_score_gemma":0.00064324465,"threshold_uncertainty_score":0.81811464},"labels":[],"label_agreement":null},{"id":"W2990908851","doi":"10.23889/ijpds.v4i3.1226","title":"Mortality of Canadian military personnel over 40 years","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Veterans Affairs Canada","funders":"","keywords":"Medicine; Demography; Population; Cause of death; Military service; Cohort; Mortality rate; Record linkage; Military personnel; Standardized mortality ratio; Disease; Environmental health; Gerontology; Surgery; Geography; Internal medicine","score_opus":0.09449596609712127,"score_gpt":0.3987046850499737,"score_spread":0.3042087189528524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990908851","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949029,0.0001025371,0.000053264932,0.00049389777,0.0028003706,0.0001196676,0.000403206,0.000004762912,0.0011193827],"genre_scores_gemma":[0.9981847,0.00007662141,0.0010248116,0.00014633454,0.00020177319,8.819816e-7,0.00019555818,0.000004127415,0.00016520277],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99883735,0.0000056690997,0.00023140335,0.00017917974,0.0006043009,0.00014210989],"domain_scores_gemma":[0.9991527,0.00001458763,0.00007083439,0.0002439729,0.00039072012,0.0001271744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047501878,0.00005078941,0.00009911364,0.0004953157,0.000088572524,0.000015606365,0.0004958665,0.000019682415,0.0002487872],"category_scores_gemma":[0.00026040082,0.000044963086,0.00005052698,0.0002584699,0.00007262254,0.0006659253,0.00007143336,0.00007189523,0.000009423279],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006810548,0.000029627083,0.9861846,0.00001380504,0.00009069577,0.000009154943,0.00047891538,0.00011850534,0.0017317758,0.0012484004,0.0047452976,0.0052811154],"study_design_scores_gemma":[0.0003388739,0.00003618742,0.9865347,0.00003649,0.000018598872,0.000033277338,0.0002996699,0.0025174886,0.00002980685,0.00015272782,0.00995391,0.000048236896],"about_ca_topic_score_codex":0.07199715,"about_ca_topic_score_gemma":0.028496368,"teacher_disagreement_score":0.04350079,"about_ca_system_score_codex":0.00012107606,"about_ca_system_score_gemma":0.00026891739,"threshold_uncertainty_score":0.98923105},"labels":[],"label_agreement":null},{"id":"W2990923113","doi":"10.23889/ijpds.v4i3.1195","title":"Poor mental health and uptake of disability benefits","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Economic and Social Research Council","keywords":"Receipt; Census; Proxy (statistics); Odds; Mental health; Population; Medicine; Odds ratio; Confounding; Demography; Gerontology; Psychology; Logistic regression; Environmental health; Psychiatry; Business","score_opus":0.08985069915564797,"score_gpt":0.4528176067581236,"score_spread":0.36296690760247563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990923113","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96593153,0.00018103971,0.000106482636,0.029216267,0.003466223,0.00028505182,0.0004962874,0.000008394111,0.0003087225],"genre_scores_gemma":[0.9964194,0.00028761505,0.001936704,0.00094967353,0.00018854596,0.0000010030084,0.00009292748,0.000002678693,0.00012142549],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984333,0.000032673146,0.00034979082,0.00018836171,0.000784983,0.0002108948],"domain_scores_gemma":[0.99911755,0.00008391958,0.00023331164,0.00014750047,0.00020633369,0.00021138092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025792143,0.000044709974,0.00010028459,0.00006491493,0.00052116957,0.00015516848,0.00080918404,0.000019550684,0.0000808533],"category_scores_gemma":[0.0007009368,0.000039708888,0.000023764562,0.00012308983,0.00025988006,0.0015942969,0.00015157298,0.000057705678,0.0000022618112],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042231015,0.00004681185,0.75632656,0.000023301216,0.000008071404,8.331018e-8,0.0015420655,0.000027255523,0.000011428791,0.16286764,0.0012522299,0.07785235],"study_design_scores_gemma":[0.00043055118,0.000050761286,0.8878413,0.0000873128,0.0000018452971,0.0000068614045,0.0025569822,0.0022476944,0.0000052148707,0.0020872387,0.10460428,0.00008000128],"about_ca_topic_score_codex":0.004098257,"about_ca_topic_score_gemma":0.0017481133,"teacher_disagreement_score":0.1607804,"about_ca_system_score_codex":0.00022929639,"about_ca_system_score_gemma":0.00043863492,"threshold_uncertainty_score":0.61953664},"labels":[],"label_agreement":null},{"id":"W2991051464","doi":"10.23889/ijpds.v4i3.1319","title":"High-dimensional propensity score adjustment in HIV research using linked administrative health data","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"AIDS Vancouver","funders":"","keywords":"Observational study; Medicine; Confounding; Context (archaeology); Propensity score matching; Population; Environmental health; Geography","score_opus":0.8021241040371514,"score_gpt":0.6189031968739147,"score_spread":0.1832209071632367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991051464","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94085234,0.000046272562,0.051955357,0.0024754796,0.0018022333,0.0015344152,0.001226942,0.000055800185,0.000051130053],"genre_scores_gemma":[0.7738064,0.000018777568,0.22479345,0.00012316699,0.0002355371,0.0000069273765,0.00090660714,0.0000141840965,0.00009495925],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9960469,0.0001642741,0.00074392377,0.0006907917,0.0019338753,0.00042025856],"domain_scores_gemma":[0.9966174,0.0004262547,0.00051854906,0.0011258905,0.0011585519,0.00015336943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077383826,0.0001391526,0.00024939273,0.0005554735,0.00032375395,0.0002466645,0.0033820025,0.000051423518,0.00007328224],"category_scores_gemma":[0.0029854525,0.00011999827,0.00002220676,0.0004798673,0.00020244086,0.004156637,0.0018046848,0.00049342896,0.00001196906],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012038779,0.001637172,0.111018725,0.00018536845,0.00014585031,0.000086350075,0.0009342891,0.006022052,0.017185263,0.7966037,0.021534352,0.043443013],"study_design_scores_gemma":[0.002219895,0.0005777281,0.11429386,0.0016472734,0.00001676368,0.00041119725,0.00034015343,0.38927305,0.0011167715,0.48779306,0.0016677957,0.0006424575],"about_ca_topic_score_codex":0.000405912,"about_ca_topic_score_gemma":0.00036494766,"teacher_disagreement_score":0.38325098,"about_ca_system_score_codex":0.0009163146,"about_ca_system_score_gemma":0.0012089484,"threshold_uncertainty_score":0.62846583},"labels":[],"label_agreement":null},{"id":"W2991133741","doi":"10.23889/ijpds.v4i3.1169","title":"The New Brunswick COPD Health Information Platform","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Obstructive Pulmonary Disease (COPD) Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"COPD; Medicine; Test (biology); Family medicine; Population; Pulmonary function testing; Pulmonary disease; Medical record; Medical prescription; Health care; Environmental health; Nursing; Internal medicine","score_opus":0.048434884166629937,"score_gpt":0.39744570245629074,"score_spread":0.3490108182896608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991133741","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8218195,0.0014684723,0.031193322,0.113434516,0.020346425,0.004841722,0.0008694246,0.00015966919,0.0058669755],"genre_scores_gemma":[0.98973316,0.0002749104,0.0033479836,0.0015577462,0.00093198917,0.0000043804694,0.0014389108,0.00001445604,0.0026964673],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9971649,0.00001577619,0.0005041101,0.00022754302,0.0017400362,0.00034760858],"domain_scores_gemma":[0.99791294,0.00011076411,0.00035092843,0.00052504335,0.0007462983,0.0003540054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016073749,0.00009727597,0.00012344496,0.00028457335,0.0005520946,0.00053839124,0.0014270293,0.00002877196,0.00015556131],"category_scores_gemma":[0.0007609193,0.00006880536,0.000058941543,0.00031285186,0.00012808421,0.0049032494,0.00033728298,0.00023862763,0.00014745104],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010913325,0.00010562547,0.18117528,0.000090704874,0.0001264771,0.0000068500017,0.0003668733,0.00062498776,0.00022046069,0.08769739,0.05715308,0.67134094],"study_design_scores_gemma":[0.0017182465,0.000101552534,0.64016,0.00010205993,0.000009080338,0.0003182551,0.00025892383,0.053058542,0.00002727159,0.0024456154,0.30169514,0.00010529323],"about_ca_topic_score_codex":0.0007695425,"about_ca_topic_score_gemma":0.00016925781,"teacher_disagreement_score":0.6712357,"about_ca_system_score_codex":0.00090322556,"about_ca_system_score_gemma":0.0041103903,"threshold_uncertainty_score":0.7291656},"labels":[],"label_agreement":null},{"id":"W2991204503","doi":"10.23889/ijpds.v4i3.1222","title":"Thriving, catching up or falling behind: Immigrant and refugee children’s kindergarten competencies and later academic achievement","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Learning Partnership; University of British Columbia","funders":"","keywords":"Refugee; Numeracy; Immigration; Thriving; Literacy; Academic achievement; Population; Developmental psychology; Longitudinal study; Psychology; Sociology; Demography; Political science; Medicine; Pedagogy","score_opus":0.047902380284165776,"score_gpt":0.38307922556363544,"score_spread":0.33517684527946967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991204503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99118745,0.000115754134,0.0004445649,0.005417414,0.0024139627,0.00027406868,0.000042703978,0.000021693659,0.00008238381],"genre_scores_gemma":[0.99328357,0.00040086667,0.0044784145,0.00053327455,0.00037968066,0.0000033164972,0.000086510874,0.0000072841726,0.000827072],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980082,0.000045025135,0.0003585771,0.00037050075,0.0009467145,0.00027097427],"domain_scores_gemma":[0.99906045,0.000117641845,0.0002505185,0.00016260434,0.00023025354,0.0001785287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002198467,0.000104371305,0.0001123991,0.0002411915,0.0009860347,0.0006823186,0.0009886217,0.000051706123,0.0000707974],"category_scores_gemma":[0.0004324699,0.00008362706,0.000020673599,0.00011003282,0.00017320961,0.0024450189,0.00030912927,0.00022623899,0.000008135355],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044391913,0.000023785124,0.95114833,0.0000040151317,0.000039714174,7.8625527e-7,0.019484155,0.000051167077,0.0002942549,0.008143113,0.00045841513,0.020307852],"study_design_scores_gemma":[0.00048911886,0.000036183625,0.9767668,0.00009483731,0.000010276772,0.000047126792,0.0024070183,0.00074303424,0.000024915194,0.0020448593,0.017156163,0.00017963965],"about_ca_topic_score_codex":0.0014141282,"about_ca_topic_score_gemma":0.001804859,"teacher_disagreement_score":0.025618475,"about_ca_system_score_codex":0.00015304273,"about_ca_system_score_gemma":0.00044738868,"threshold_uncertainty_score":0.75838816},"labels":[],"label_agreement":null},{"id":"W2991214189","doi":"10.23889/ijpds.v4i3.1288","title":"One Size Doesn’t Fit All: Administrative Data Quality Frameworks for Production of Official Statistics","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"","keywords":"Quality (philosophy); Respondent; Computer science; Data quality; Quality assurance; Official statistics; Production (economics); Presentation (obstetrics); Data science; Statistics; Business; Marketing; Mathematics; Economics; Service (business); Political science","score_opus":0.5213838774143231,"score_gpt":0.5630043009073256,"score_spread":0.041620423493002434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991214189","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30210495,0.000020943764,0.6777717,0.0038426802,0.008056901,0.0006543968,0.007468015,0.000018429067,0.000061979255],"genre_scores_gemma":[0.88347465,0.000025733987,0.114033125,0.00018897769,0.00042190775,0.000005630693,0.0015575159,0.0000088766665,0.00028359852],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9944105,0.00009934343,0.0013677516,0.00083677494,0.0030530312,0.00023261247],"domain_scores_gemma":[0.9914149,0.0022220863,0.0014465399,0.001360364,0.0034444393,0.00011168009],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.011674725,0.0001221746,0.00026138796,0.00032631657,0.00026267782,0.0005703817,0.004444408,0.00009486475,0.00011853431],"category_scores_gemma":[0.032083534,0.000101442696,0.00006178465,0.0004810233,0.00023245055,0.0035585067,0.00045936668,0.00023133526,0.000011762542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0048633013,0.0019357161,0.089126736,0.000117599346,0.0006226068,0.0000030177137,0.0027203404,0.06455418,0.014901183,0.264174,0.04667132,0.51031],"study_design_scores_gemma":[0.0012243659,0.0003313949,0.14088227,0.00012457202,0.000075902426,0.000022161457,0.0015173986,0.59610194,0.0003090992,0.24690053,0.012129132,0.00038123372],"about_ca_topic_score_codex":0.000096618474,"about_ca_topic_score_gemma":0.00021459314,"teacher_disagreement_score":0.5813697,"about_ca_system_score_codex":0.0000704367,"about_ca_system_score_gemma":0.00038562657,"threshold_uncertainty_score":0.9760696},"labels":[],"label_agreement":null},{"id":"W2991257253","doi":"10.23889/ijpds.v4i3.1254","title":"Educational outcomes of children in Wales with cerebral palsy","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cerebral Palsy and Movement Disorders","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cerebral palsy; Attendance; Medicine; Pediatrics; Family medicine; Special education; Special educational needs; Census; Curriculum; Socioeconomic status; Quarter (Canadian coin); Psychology; Demography; Geography; Pedagogy; Physical therapy; Environmental health; Population","score_opus":0.030433032264506228,"score_gpt":0.36300657724858115,"score_spread":0.33257354498407493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991257253","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943317,0.000026385915,0.00020167374,0.0041010273,0.0005520268,0.00030483527,0.00010996543,0.000004087286,0.0003682741],"genre_scores_gemma":[0.9955718,0.000010839105,0.002931466,0.0003682715,0.00007812455,0.000003116654,0.0005714809,0.0000054812817,0.00045941153],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986437,0.000008147667,0.00031233742,0.0002152271,0.00068961235,0.00013095993],"domain_scores_gemma":[0.99919623,0.00004941956,0.00019794228,0.00023419523,0.00026207662,0.000060143324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045357153,0.0000714283,0.00013952772,0.00032697615,0.000048768306,0.000046170975,0.000565696,0.000019188357,0.00024491953],"category_scores_gemma":[0.00022988237,0.000051990846,0.000035063396,0.0001896218,0.00007750716,0.0009967146,0.00008434901,0.00008504777,0.0000065084328],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010637318,0.0001138935,0.99240714,0.0000057439256,0.000034479424,3.496848e-7,0.0000374262,0.00013155134,0.00028347308,0.0051092315,0.00018779682,0.0015825665],"study_design_scores_gemma":[0.0016324768,0.00008079995,0.99578655,0.000077704404,0.000011607322,0.000045124852,0.000056987126,0.0009122468,0.0000785302,0.0010227485,0.00023217434,0.00006304853],"about_ca_topic_score_codex":0.00024335738,"about_ca_topic_score_gemma":0.00018488147,"teacher_disagreement_score":0.0040864833,"about_ca_system_score_codex":0.00007313631,"about_ca_system_score_gemma":0.00024780043,"threshold_uncertainty_score":0.2681697},"labels":[],"label_agreement":null},{"id":"W2991298179","doi":"10.23889/ijpds.v4i3.1229","title":"Exploratory Research on the Health and Social Outcomes of Public Housing","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"","keywords":"Public housing; Government (linguistics); Public health; Cohort; Emergency department; Exploratory research; Criminal justice; Medicine; Economic Justice; Business; Demography; Gerontology; Environmental health; Medical emergency; Psychology; Political science; Economics; Nursing; Economic growth; Sociology; Criminology","score_opus":0.5133545564755552,"score_gpt":0.5680958035699084,"score_spread":0.05474124709435324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991298179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85880893,0.00005154306,0.00019176336,0.13811153,0.0019976743,0.00026706757,0.00007932932,0.000008355929,0.0004838052],"genre_scores_gemma":[0.9968775,0.00009056595,0.00022966288,0.002395753,0.00025691165,0.0000027425779,0.000017750643,0.000003826924,0.00012532249],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9973744,0.00025552863,0.0002833545,0.00017505365,0.001589411,0.00032222894],"domain_scores_gemma":[0.99820536,0.00067142496,0.00021430512,0.00016579923,0.00061441056,0.00012868328],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0123848375,0.000043910884,0.00010077783,0.0002547466,0.0018470313,0.00044068886,0.0012776547,0.00002446092,0.0000458611],"category_scores_gemma":[0.0020823122,0.000030480378,0.00002481144,0.00026511855,0.0004051158,0.0014857224,0.00021530392,0.00016852516,0.0000049636024],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015216281,0.000025492121,0.34471676,0.000009908023,0.0000091046195,2.0476632e-7,0.0034091016,0.0000037820541,0.0000041841417,0.63616264,0.0026729922,0.012970596],"study_design_scores_gemma":[0.0005704302,0.00012306764,0.7438998,0.00010706643,0.0000024923982,0.0000027039346,0.04732186,0.0012348582,0.0000064240494,0.015962731,0.1906173,0.00015125652],"about_ca_topic_score_codex":0.0013181415,"about_ca_topic_score_gemma":0.00085358805,"teacher_disagreement_score":0.6201999,"about_ca_system_score_codex":0.00023908797,"about_ca_system_score_gemma":0.0010505497,"threshold_uncertainty_score":0.9994524},"labels":[],"label_agreement":null},{"id":"W2991862006","doi":"10.23889/ijpds.v4i1.1124","title":"Concept Dictionary and Glossary at MCHP","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Glossary; Documentation; Computer science; Consistency (knowledge bases); Globe; Data science; Government (linguistics); Knowledge management; Terminology; World Wide Web; Artificial intelligence; Linguistics; Psychology","score_opus":0.3181216733610139,"score_gpt":0.5508663089012783,"score_spread":0.23274463554026442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991862006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95042557,0.00016385512,0.009459588,0.012576015,0.019664837,0.0009143917,0.00066212565,0.000076685785,0.0060569197],"genre_scores_gemma":[0.9909001,0.000106763146,0.002260209,0.0027153213,0.0008960082,0.000009743626,0.00074989296,0.0000066456614,0.0023553],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99808633,0.000053711392,0.00055002933,0.00022350806,0.0008281164,0.0002583023],"domain_scores_gemma":[0.9983858,0.00030897613,0.00038288653,0.00023908357,0.00047549815,0.00020777967],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0022125735,0.00006872524,0.00010094184,0.00019264431,0.0013011664,0.00005653145,0.0007143626,0.000064006046,0.00066288374],"category_scores_gemma":[0.00093152444,0.00005654905,0.0000179245,0.00012487845,0.00009994467,0.002191358,0.00044400766,0.00029107524,0.00015774084],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037623933,0.0000451584,0.80870557,0.00012085088,0.000035046833,0.000003508372,0.0022252093,0.00027354035,0.00055844744,0.043017548,0.090288065,0.05435081],"study_design_scores_gemma":[0.0016027134,0.00008917529,0.52638346,0.0002469075,0.000009160548,0.00008810816,0.0004970736,0.08854513,0.000009525862,0.002884122,0.37949052,0.00015409569],"about_ca_topic_score_codex":0.00008990662,"about_ca_topic_score_gemma":0.000018776747,"teacher_disagreement_score":0.28920245,"about_ca_system_score_codex":0.00036337337,"about_ca_system_score_gemma":0.00029995365,"threshold_uncertainty_score":0.999999},"labels":[],"label_agreement":null},{"id":"W2993629479","doi":"10.23889/ijpds.v4i1.1116","title":"Achieving cross provincial comparisons of osteoporosis screening performance from administrative health data.","year":2019,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; University of Waterloo; Western University","funders":"","keywords":"Operationalization; Identification (biology); Flexibility (engineering); Health care; Work (physics); Computer science; Political science; Engineering; Statistics","score_opus":0.5093538756730761,"score_gpt":0.6014346457643377,"score_spread":0.09208077009126159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2993629479","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95880854,0.000028497721,0.03254287,0.0035785835,0.0016684292,0.00049054815,0.0028252853,0.000013468409,0.000043750148],"genre_scores_gemma":[0.9070499,0.0000282403,0.08556597,0.0004523164,0.0004846646,0.0000018689769,0.0063733594,0.000008820939,0.000034862605],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967406,0.00004595872,0.0012928445,0.00045836673,0.0012616387,0.00020062889],"domain_scores_gemma":[0.99634314,0.0005048623,0.0013950788,0.00071293116,0.0008933716,0.00015062082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003653707,0.00009959668,0.00024145952,0.00017552137,0.00025836247,0.0002107535,0.0015708981,0.000031364838,0.00011952608],"category_scores_gemma":[0.0042043235,0.00008988737,0.00004053906,0.00020689824,0.00012899192,0.0045956983,0.00064471713,0.00024167611,0.000008893254],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059311814,0.000108265085,0.93912286,0.000020174599,0.00005089473,9.892751e-7,0.00012413911,0.0004150082,0.0012728403,0.000106193605,0.001310999,0.056874543],"study_design_scores_gemma":[0.0016469231,0.000325332,0.8583198,0.00019927233,0.000033540524,0.000048832997,0.00043170288,0.133837,0.00016446048,0.000028068114,0.004874714,0.000090327114],"about_ca_topic_score_codex":0.0013264461,"about_ca_topic_score_gemma":0.00031535595,"teacher_disagreement_score":0.13342199,"about_ca_system_score_codex":0.00015811808,"about_ca_system_score_gemma":0.0010174601,"threshold_uncertainty_score":0.5033272},"labels":[],"label_agreement":null},{"id":"W3003985767","doi":"10.23889/ijpds.v5i1.1123","title":"Unlocking the Potential of Electronic Health Records for Health Research","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health; University of Calgary; Alberta Health Services","funders":"","keywords":"Health records; Electronic health record; Data science; Computer science; Health care; Political science","score_opus":0.45049565642723766,"score_gpt":0.6276072710141566,"score_spread":0.17711161458691893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003985767","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06527045,0.001530677,0.3414319,0.57074577,0.012580416,0.006760231,0.0014177288,0.0000834045,0.0001794404],"genre_scores_gemma":[0.98684496,0.00040355764,0.0033383348,0.0058753407,0.0029398534,0.00009062278,0.00030936854,0.000026524089,0.0001714337],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9939699,0.000888394,0.0015578028,0.0004913578,0.0017856618,0.001306858],"domain_scores_gemma":[0.9945871,0.0010612592,0.0014177923,0.0004752963,0.0020774405,0.00038110197],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.027132684,0.00011254065,0.00029041263,0.0003178176,0.0033907206,0.00008940218,0.0030403633,0.00006132835,0.000041785297],"category_scores_gemma":[0.0048184595,0.00008435882,0.000071286406,0.00073691923,0.00015570296,0.0009225232,0.00043070476,0.0010720486,0.000010197315],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023059654,0.00026262447,0.043359905,0.0015254938,0.000247937,0.0000023231917,0.009964,0.00275559,0.0018009617,0.20131564,0.41633153,0.32012805],"study_design_scores_gemma":[0.0029119002,0.0022269753,0.024107242,0.0008204032,0.000011887279,0.000057853435,0.0038638802,0.2601083,0.000029333896,0.015123928,0.69046926,0.00026900033],"about_ca_topic_score_codex":0.001954107,"about_ca_topic_score_gemma":0.0011735179,"teacher_disagreement_score":0.92157453,"about_ca_system_score_codex":0.0017498903,"about_ca_system_score_gemma":0.010921626,"threshold_uncertainty_score":0.99790674},"labels":[],"label_agreement":null},{"id":"W3006968785","doi":"10.23889/ijpds.v5i1.1144","title":"Developing a comprehensive database with sensitive health information: A profile of people living with HIV in Newfoundland and Labrador, Canada","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"HIV/AIDS Research and Interventions","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bruyère; University of Ottawa; St. John’s Health Sciences Centre; Newfoundland and Labrador Centre for Applied Health Research; Memorial University of Newfoundland","funders":"Canadian Institutes of Health Research","keywords":"Confidentiality; Cohort; Database; Computer science; Context (archaeology); Data governance; Population; Medical record; Health care; Medicine; Data quality; Business; Environmental health; Geography; Computer security; Political science","score_opus":0.053734780136221696,"score_gpt":0.36647064860018286,"score_spread":0.3127358684639612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006968785","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87808853,0.000039529248,0.09903244,0.02071952,0.00007546345,0.0005671222,0.0013596528,0.000008463108,0.00010927044],"genre_scores_gemma":[0.9778125,0.000027594937,0.020675534,0.00065567606,0.000048467693,0.000004364819,0.00074092083,0.00000379807,0.00003112901],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986718,0.000023701463,0.00030222285,0.00014700192,0.0006939535,0.0001612635],"domain_scores_gemma":[0.99862075,0.0000838689,0.00021081655,0.00010762192,0.0007835073,0.00019345935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003406003,0.00006318381,0.00013810238,0.00019369283,0.00013504202,0.00009538743,0.0002353949,0.000008367069,0.000016256503],"category_scores_gemma":[0.0005875404,0.000046999125,0.000009303422,0.0003707799,0.0000726643,0.0019651141,0.00014269543,0.00012573191,5.7678733e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012829243,0.00009162211,0.95598465,0.0005009174,0.00015583512,0.00005562026,0.0051588067,0.00049352023,0.0003972405,0.004396774,0.0084855845,0.022996495],"study_design_scores_gemma":[0.0020298662,0.0008584732,0.8705694,0.0016848108,0.000010638862,0.00063889043,0.0034589241,0.11745408,0.000044278342,0.000011917443,0.0031169474,0.00012177939],"about_ca_topic_score_codex":0.1278476,"about_ca_topic_score_gemma":0.33581004,"teacher_disagreement_score":0.20796245,"about_ca_system_score_codex":0.0003116297,"about_ca_system_score_gemma":0.0022952782,"threshold_uncertainty_score":0.87796015},"labels":[],"label_agreement":null},{"id":"W3008599113","doi":"10.23889/ijpds.v5i1.1145","title":"The Mortality After Release from Incarceration Consortium (MARIC): Protocol for a multi-national, individual participant data meta-analysis","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Criminal Justice and Corrections Analysis","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Provincial Health Services Authority; McMaster University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Economic and Social Research Council; World Health Organization","keywords":"Protocol (science); Meta-analysis; Computer science; Medicine; Internal medicine","score_opus":0.7107215386385041,"score_gpt":0.5645774302861782,"score_spread":0.14614410835232583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008599113","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031725377,0.0003471628,0.8224364,0.04364182,0.002531983,0.064254485,0.034704007,0.00018137193,0.00017740049],"genre_scores_gemma":[0.9612318,0.00002220221,0.014037545,0.0015771587,0.0014626995,0.01831485,0.0032248036,0.000014158472,0.00011473414],"study_design_codex":"meta_analysis","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99578327,0.00020639265,0.000788738,0.00068560225,0.0022299078,0.0003060935],"domain_scores_gemma":[0.99595696,0.000618699,0.00064006535,0.00062719797,0.0019031028,0.0002539722],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0050205183,0.00014110896,0.0002859332,0.00021561915,0.0021577938,0.002036864,0.0035789958,0.00005091884,0.00025599007],"category_scores_gemma":[0.0075213364,0.000102783706,0.00032824642,0.0009724244,0.00034231498,0.003261255,0.00058851566,0.00015940514,0.0000070432757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0066753505,0.0033360426,0.17460153,0.00011324213,0.39736247,0.00006377131,0.05352298,0.06514375,0.0005242702,0.05798567,0.09150251,0.1491684],"study_design_scores_gemma":[0.0007956678,0.000043921485,0.025030462,0.000005438563,0.075360335,0.0000018147205,0.008461843,0.80135417,0.000013429142,0.0013425072,0.087285794,0.00030464306],"about_ca_topic_score_codex":0.005993094,"about_ca_topic_score_gemma":0.032015063,"teacher_disagreement_score":0.9295065,"about_ca_system_score_codex":0.000105215964,"about_ca_system_score_gemma":0.0007930768,"threshold_uncertainty_score":0.9991413},"labels":[],"label_agreement":null},{"id":"W3008772783","doi":"10.23889/ijpds.v5i1.1125","title":"Empowering knowledge generation through international data network: the IMeCCHI-DATANETWORK","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute of Aging; University of Calgary","funders":"","keywords":"Computer science; Knowledge management; Data science; Business","score_opus":0.6799564508401671,"score_gpt":0.6048093947187827,"score_spread":0.07514705612138439,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008772783","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009031088,0.00053768686,0.8211393,0.10156836,0.05799364,0.001507851,0.0016408197,0.0001904768,0.006390792],"genre_scores_gemma":[0.8882033,0.00086054456,0.03364133,0.019316845,0.04079693,0.000046718178,0.016702447,0.000037840797,0.00039400187],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996532,0.00018048658,0.0011552572,0.0005070006,0.0011205637,0.00050464633],"domain_scores_gemma":[0.9967249,0.00046900133,0.00078585447,0.00085690286,0.0009043873,0.0002589775],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0058795717,0.00014765427,0.00016681674,0.00008795066,0.0028390011,0.00033214965,0.0061739,0.000091807866,0.00038151196],"category_scores_gemma":[0.004295929,0.000107262735,0.000035420224,0.00042041249,0.0001323524,0.0053560017,0.0021734873,0.0007542064,0.00014890611],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002490603,0.00005287204,0.016425485,0.000055758843,0.000109814006,0.000003724247,0.0046552736,0.00700011,0.00017026064,0.037950188,0.8431946,0.090132825],"study_design_scores_gemma":[0.00037787127,0.00001887167,0.0024957147,0.00007315642,0.000011019181,0.000011165879,0.00020865779,0.51285166,0.0000017237481,0.0005966143,0.48326924,0.00008431465],"about_ca_topic_score_codex":0.000103251456,"about_ca_topic_score_gemma":0.00013126996,"teacher_disagreement_score":0.87917227,"about_ca_system_score_codex":0.0002384071,"about_ca_system_score_gemma":0.00078285835,"threshold_uncertainty_score":0.99920315},"labels":[],"label_agreement":null},{"id":"W3008875173","doi":"10.23889/ijpds.v5i1.1147","title":"Immigrant and ethnic neighbourhood concentration and reduced child developmental vulnerability","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; University of Manitoba; McMaster University; University of Saskatchewan","funders":"Canadian Institutes of Health Research","keywords":"Neighbourhood (mathematics); Socioeconomic status; Demography; Ethnic group; Social vulnerability; Child development; Psychology; Population; Immigration; Developmental psychology; Geography; Psychological intervention; Sociology","score_opus":0.12054267205774166,"score_gpt":0.39964911361861527,"score_spread":0.2791064415608736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008875173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9521514,0.00057251356,0.0072102034,0.03521599,0.0018560471,0.00051712134,0.0002516674,0.000060758994,0.0021642789],"genre_scores_gemma":[0.99588865,0.00046098558,0.0023252424,0.0006711878,0.0005343094,0.000004361875,0.00007708727,0.0000045979036,0.000033551583],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998223,0.00007011282,0.00033837324,0.00037715535,0.00078372925,0.00020760696],"domain_scores_gemma":[0.9989349,0.00014064583,0.00020000311,0.00008603362,0.00040321532,0.00023518644],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0013437895,0.00009293434,0.00011665844,0.00005438597,0.0015263779,0.00048314198,0.00060828426,0.000037372978,0.000056466793],"category_scores_gemma":[0.0024331359,0.000084807536,0.000022179493,0.0002591496,0.00044591815,0.0023900266,0.00019529698,0.00013553028,0.0000023358123],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046050586,0.00019296572,0.43305844,0.00003329496,0.00023594966,0.000011335434,0.082881786,0.00012555973,0.0061547193,0.14493923,0.0036400945,0.3282661],"study_design_scores_gemma":[0.0015724299,0.00009635767,0.9409124,0.00005901989,0.000036793845,0.000063300744,0.008687916,0.017743545,0.00024081573,0.0040863925,0.026109945,0.0003910615],"about_ca_topic_score_codex":0.0005736312,"about_ca_topic_score_gemma":0.0005324278,"teacher_disagreement_score":0.507854,"about_ca_system_score_codex":0.000121421304,"about_ca_system_score_gemma":0.00022040385,"threshold_uncertainty_score":0.9997735},"labels":[],"label_agreement":null},{"id":"W3012405341","doi":"10.23889/ijpds.v4i2.1135","title":"ICES: Data, Discovery, Better Health","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":128,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Ontario Ministry of Health and Long-Term Care","keywords":"Health care; Indigenous; Community health; Population health; Health policy; Business; Population; Medicine; Public relations; Environmental health; Political science; Economic growth; Economics","score_opus":0.3364591803734862,"score_gpt":0.5670953455288539,"score_spread":0.23063616515536767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012405341","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041259017,0.00039501447,0.13195024,0.79227793,0.020501997,0.0013504246,0.010346182,0.00014931239,0.0017698873],"genre_scores_gemma":[0.54821765,0.00049213663,0.031219881,0.39731917,0.009636609,0.000023905053,0.012162972,0.000045445744,0.00088221714],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99689263,0.00012261822,0.00086433894,0.00056121196,0.0010831098,0.00047606434],"domain_scores_gemma":[0.99744827,0.00028944845,0.0006776858,0.00077813386,0.00043526548,0.0003711812],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0027733773,0.000114096045,0.0002073423,0.00016378348,0.0014965184,0.00023561221,0.0048393393,0.00004650599,0.00022164117],"category_scores_gemma":[0.0015180575,0.00009381883,0.000034433233,0.00026742005,0.00007918162,0.007423012,0.0017854762,0.00046404422,0.000096764736],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013753926,0.00003633258,0.2622214,0.00008804264,0.00003808666,0.0000067629376,0.00084023847,0.00003191105,0.0000911022,0.006509042,0.6895135,0.040486027],"study_design_scores_gemma":[0.0008178913,0.00006918795,0.13510863,0.00007255547,0.000010311685,0.000012925327,0.00033062228,0.010501132,0.0000017811662,0.001376848,0.85154706,0.00015105604],"about_ca_topic_score_codex":0.00066431775,"about_ca_topic_score_gemma":0.0003847449,"teacher_disagreement_score":0.50695866,"about_ca_system_score_codex":0.0005113112,"about_ca_system_score_gemma":0.0027776256,"threshold_uncertainty_score":0.9998034},"labels":[],"label_agreement":null},{"id":"W3014051546","doi":"10.23889/ijpds.v5i1.1155","title":"Is there an agreement between self-reported medical diagnosis in the CARTaGENE cohort and the Québec administrative health databases?","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal; McGill University Health Centre; McGill University; Centre Hospitalier Universitaire Sainte-Justine","funders":"","keywords":"Concordance; Medicine; Logistic regression; Cohen's kappa; Kappa; Cohort; Medical record; Population; Database; Demography; Family medicine; Gerontology; Statistics; Environmental health; Internal medicine","score_opus":0.19508709330881696,"score_gpt":0.47367252900248025,"score_spread":0.2785854356936633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3014051546","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8254994,0.0003889062,0.0017737014,0.16797782,0.00028889434,0.0009854789,0.0029937287,0.000024237,0.000067837915],"genre_scores_gemma":[0.9882386,0.00040044723,0.0010243901,0.007747154,0.00044975808,0.000029636067,0.0020977994,0.0000064643505,0.000005756118],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967778,0.00018338319,0.0005919678,0.0004182157,0.0018417552,0.00018688918],"domain_scores_gemma":[0.9981365,0.00035697818,0.00038353688,0.00051190297,0.0002592396,0.0003518124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041710474,0.00010848395,0.00021246592,0.000075373646,0.00029478667,0.0001774505,0.001366929,0.000019425906,0.0001477499],"category_scores_gemma":[0.0025658065,0.00006189691,0.000037798116,0.00026634542,0.0002816847,0.00094333885,0.00028030938,0.00023243873,0.0000037435962],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013904626,0.00008313984,0.98596424,0.000009937228,0.00013670305,0.00004189921,0.0009417067,0.000004782743,0.000002167315,0.0004895901,0.0046071107,0.007579674],"study_design_scores_gemma":[0.0015834898,0.00012336018,0.965888,0.00006724768,0.000068292306,0.00012442234,0.00037765087,0.011517796,0.000007725926,0.00007336964,0.02009431,0.00007433937],"about_ca_topic_score_codex":0.0054724594,"about_ca_topic_score_gemma":0.0056415587,"teacher_disagreement_score":0.1627392,"about_ca_system_score_codex":0.0001418291,"about_ca_system_score_gemma":0.0013601921,"threshold_uncertainty_score":0.82727575},"labels":[],"label_agreement":null},{"id":"W3014193862","doi":"10.23889/ijpds.v5i1.1156","title":"The effect of number of healthcare visits on study sample selection in electronic health record data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"National Center for Advancing Translational Sciences; National Center for Chronic Disease Prevention and Health Promotion","keywords":"Medicine; Sample (material); Health care; Electronic health record; Sample size determination; Family medicine; Gerontology; Statistics","score_opus":0.338917648568192,"score_gpt":0.5860153991181046,"score_spread":0.24709775054991262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3014193862","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9423104,0.00006542881,0.013256375,0.038608346,0.0024257053,0.0023766644,0.00084106426,0.000029815175,0.0000862001],"genre_scores_gemma":[0.9978133,0.00012249737,0.0005504941,0.00079609116,0.00031488296,0.000014605904,0.00037385584,0.000006186556,0.000008085451],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9965693,0.0005112574,0.0012316027,0.00026775562,0.0010614743,0.00035861292],"domain_scores_gemma":[0.99650764,0.0014546417,0.0011227282,0.0003427824,0.0004068674,0.0001653576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010183314,0.000081521925,0.00021605786,0.00014831299,0.0008444205,0.00002851933,0.0017638246,0.00004121251,0.00003067643],"category_scores_gemma":[0.00732583,0.000055872086,0.000019576375,0.0005015239,0.000040743038,0.0009271632,0.0003192218,0.0005859801,0.000007343183],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010052883,0.000052621584,0.89915603,0.00017058974,0.000017865343,2.0530214e-7,0.0010706765,0.00017390368,0.000012795938,0.0044170795,0.003337139,0.09058579],"study_design_scores_gemma":[0.005183277,0.005357985,0.6301221,0.00096408615,0.00002104988,0.000010850651,0.0023876086,0.30957884,0.000027839716,0.0016886065,0.044435382,0.00022238768],"about_ca_topic_score_codex":0.003373752,"about_ca_topic_score_gemma":0.002772216,"teacher_disagreement_score":0.30940494,"about_ca_system_score_codex":0.00038901588,"about_ca_system_score_gemma":0.0010513382,"threshold_uncertainty_score":0.8770232},"labels":[],"label_agreement":null},{"id":"W3037903189","doi":"10.23889/ijpds.v5i1.1158","title":"Community-based Health Data Cooperatives Towards Improving the Immigrant Community Health: A Scoping Review to Inform Policy and Practice","year":2020,"lang":"en","type":"review","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre; University of Calgary","funders":"","keywords":"Grey literature; The Internet; Business; Knowledge management; Community health; Key (lock); Thematic analysis; Government (linguistics); Computer science; Data science; World Wide Web; Medicine; MEDLINE; Qualitative research; Sociology; Political science; Public health; Computer security; Nursing","score_opus":0.45194414515102554,"score_gpt":0.6023907905946787,"score_spread":0.15044664544365316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037903189","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00000322707,0.9125678,0.010762557,0.06684975,0.0014236366,0.0034941186,0.004790353,0.00003468327,0.000073861855],"genre_scores_gemma":[0.000092361064,0.94597274,0.005861103,0.036895853,0.0006030684,0.000095553485,0.010424969,0.000030258945,0.000024064711],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9924333,0.0033674054,0.0020407506,0.0005513728,0.001073995,0.0005331736],"domain_scores_gemma":[0.9913612,0.002272575,0.0025214953,0.002417126,0.0008248932,0.000602724],"candidate_categories":["metaresearch","metaepi_narrow","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.025187718,0.0003458044,0.0010187182,0.00052119675,0.0043500853,0.0008180847,0.0073459544,0.00007911179,0.00002343932],"category_scores_gemma":[0.015286153,0.0002456654,0.00009202728,0.0012909838,0.00023053453,0.0025078966,0.0018698986,0.0018161468,0.00001835037],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004168068,0.000082295104,0.000004068507,0.012199653,0.000058421076,0.0000013182618,0.0026338955,0.0000029973507,4.193867e-8,0.0017579425,0.005830016,0.97738767],"study_design_scores_gemma":[0.00031557638,0.00027924505,0.00012861339,0.06643595,0.0000732086,0.00058334466,0.0007571892,0.0003406857,1.7891171e-8,0.00002836546,0.9308472,0.0002105559],"about_ca_topic_score_codex":0.039983064,"about_ca_topic_score_gemma":0.009885553,"teacher_disagreement_score":0.97717714,"about_ca_system_score_codex":0.000660195,"about_ca_system_score_gemma":0.009789897,"threshold_uncertainty_score":0.9999996},"labels":[],"label_agreement":null},{"id":"W3047731084","doi":"10.23889/ijpds.v5i2.1383","title":"Prospective data linkage to facilitate COVID-19 trials – A call to action","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Institute for Work & Health; Process Simulations Limited (Canada); British Columbia Environmental and Occupational Health Research Network; University of Toronto","funders":"Medical Research Council","keywords":"Coronavirus disease 2019 (COVID-19); Linkage (software); Call to action; Record linkage; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Clinical trial; Data science; Computer science; Business; Medicine; Outbreak; Biology; Virology; Marketing; Environmental health; Internal medicine; Disease; Infectious disease (medical specialty)","score_opus":0.8802420608172462,"score_gpt":0.6327254420537285,"score_spread":0.24751661876351772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3047731084","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0075198244,0.00000958035,0.86405563,0.11138661,0.0034739235,0.0010337427,0.012256146,0.00004530521,0.00021922536],"genre_scores_gemma":[0.8836847,0.00003122626,0.06844719,0.040288433,0.002151767,0.00004777874,0.0034792665,0.000019493844,0.0018501598],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99262196,0.00031873884,0.0014299708,0.0013610531,0.003968605,0.00029964867],"domain_scores_gemma":[0.99399996,0.0014138996,0.00069541304,0.0016853554,0.0011253739,0.001079986],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.031338584,0.00014820954,0.0003258152,0.00065902295,0.00058853265,0.0026617672,0.012075407,0.000034761382,0.00026853342],"category_scores_gemma":[0.18396075,0.0001154389,0.000069857575,0.0013766747,0.00009299644,0.007204645,0.0043573673,0.00016606803,0.00042940828],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090804923,0.00009584885,0.0040021306,0.00001039618,0.00007645728,0.000019091049,0.0022104238,0.009780368,0.001421906,0.008722223,0.8373232,0.13542993],"study_design_scores_gemma":[0.00070816267,0.00014407972,0.011700107,0.000015026118,0.000019655628,0.000017687893,0.00085943897,0.033319835,0.000052961426,0.008883944,0.9440779,0.00020118589],"about_ca_topic_score_codex":0.0004403982,"about_ca_topic_score_gemma":0.00046272684,"teacher_disagreement_score":0.87616485,"about_ca_system_score_codex":0.00033315623,"about_ca_system_score_gemma":0.00045637146,"threshold_uncertainty_score":0.99837357},"labels":[],"label_agreement":null},{"id":"W3048799016","doi":"10.23889/ijpds.v5i1.1340","title":"Development of comparable algorithms to measure primary care indicators using administrative health data across three Canadian provinces","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Montfort Hospital; Bruyère; University of Ottawa; Dalhousie University; University of British Columbia; Western University; University of Waterloo","funders":"Canadian Institutes of Health Research; Health Canada; Michael Smith Health Research BC; Dalhousie University; Nova Scotia Department of Health and Wellness; Ontario Ministry of Health and Long-Term Care; Department of Health, Western Cape Government","keywords":"Comparability; Performance indicator; Health care; Work (physics); Health indicator; Computer science; Business; Political science; Engineering; Marketing","score_opus":0.5058754779513256,"score_gpt":0.5708277109988958,"score_spread":0.06495223304757025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3048799016","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72133327,0.0011058041,0.14301397,0.07177219,0.012704056,0.006279444,0.041889526,0.0001254229,0.0017763518],"genre_scores_gemma":[0.81999594,0.000014948946,0.16235448,0.012504286,0.0006247351,0.000015277907,0.00445358,0.000018469793,0.000018272509],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9965909,0.0000815577,0.0010571439,0.00051234075,0.0011894205,0.0005686496],"domain_scores_gemma":[0.99694073,0.00010443125,0.00078735256,0.00049471617,0.0008455425,0.00082720467],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0025835,0.0001328582,0.00029191654,0.0002912468,0.0022097519,0.000092998474,0.0035056567,0.00005748619,0.00003308856],"category_scores_gemma":[0.0005898447,0.0001188773,0.000023001334,0.00053141994,0.00008750936,0.001800036,0.0010566687,0.0003460263,0.000009240978],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004123523,0.00006854689,0.6119719,0.00070241326,0.0001501628,0.000014223476,0.05332249,0.00032164445,0.00027978022,0.0013409185,0.023003576,0.308412],"study_design_scores_gemma":[0.001619899,0.0002191815,0.6124887,0.00072668603,0.00002384788,0.000020951898,0.016917448,0.010736517,0.00005919646,0.00013219916,0.3565491,0.00050628115],"about_ca_topic_score_codex":0.021856112,"about_ca_topic_score_gemma":0.19545124,"teacher_disagreement_score":0.33354557,"about_ca_system_score_codex":0.0028542606,"about_ca_system_score_gemma":0.034554444,"threshold_uncertainty_score":0.99908924},"labels":[],"label_agreement":null},{"id":"W3049257903","doi":"10.23889/ijpds.v5i1.1150","title":"Effect of Study Duration and Outcome Measurement Frequency on Estimates of Change for Longitudinal Cohort Studies in Routinely-Collected Administrative Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba; CancerCare Manitoba","funders":"University of Manitoba","keywords":"Cohort; Statistics; Duration (music); Cohort study; Linear regression; Demography; Medicine; Longitudinal study; Repeated measures design; Standard error; Regression analysis; Psychology; Mathematics","score_opus":0.88409621524642,"score_gpt":0.6454970174625501,"score_spread":0.23859919778386995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3049257903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99351424,0.0000879592,0.0028341888,0.0011236635,0.00077826105,0.0011730475,0.00047003984,0.000006678079,0.0000119017095],"genre_scores_gemma":[0.99550766,0.000028304523,0.004166248,0.000029081728,0.00013281671,0.000031422984,0.00009871307,0.0000033689012,0.0000023937612],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968128,0.0011476793,0.0006322635,0.00036590357,0.0009061001,0.00013522751],"domain_scores_gemma":[0.994103,0.0042585353,0.0005173256,0.00020813906,0.00084923557,0.00006375112],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.04189762,0.00008660344,0.00025362874,0.00019551165,0.00028838273,0.000050638966,0.0010306666,0.000030303107,0.000005719801],"category_scores_gemma":[0.112212956,0.000070392576,0.000021595104,0.00034975403,0.00031111191,0.0011851158,0.00018129307,0.000081589,1.7457661e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027771117,0.000085223866,0.9914028,0.000018355688,0.000095832,0.0000026688163,0.0029121595,0.000011152632,0.00039619848,0.0006125968,0.000035508703,0.0016504047],"study_design_scores_gemma":[0.0010086611,0.0011293583,0.99289095,0.000060563256,0.000058269467,0.0000025588638,0.0010305968,0.002882162,0.00040060826,0.00044117394,0.000021712716,0.00007338697],"about_ca_topic_score_codex":0.0005567912,"about_ca_topic_score_gemma":0.002155853,"teacher_disagreement_score":0.07031533,"about_ca_system_score_codex":0.000113810485,"about_ca_system_score_gemma":0.00018285749,"threshold_uncertainty_score":0.98656803},"labels":[],"label_agreement":null},{"id":"W3080320223","doi":"10.23889/ijpds.v5i1.1353","title":"Essential Requirements for Establishing and Operating Data Trusts","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; MaRS; University of British Columbia; Compute Canada; Hospital for Sick Children; BC Centre for Disease Control; Sunnybrook Health Science Centre; British Columbia Environmental and Occupational Health Research Network; Canadian Institute for Health Information; McGill University and Génome Québec Innovation Centre; St. Joseph's Care Group; Institute for Work & Health; Ontario Genomics; Sunnybrook Hospital; Vector Institute; SickKids Foundation; University Health Network; University of Toronto","funders":"Terry Fox Research Institute","keywords":"Computer science; Business; Process management; Risk analysis (engineering); Data science","score_opus":0.7775022628649542,"score_gpt":0.6687863492661111,"score_spread":0.10871591359884303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080320223","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4495665,0.00016686342,0.37786388,0.16076133,0.005287547,0.0019008943,0.0039321813,0.000072354764,0.0004484356],"genre_scores_gemma":[0.9100857,0.000081952385,0.08479992,0.0019384485,0.0015135914,0.0000045669067,0.001435342,0.000012385193,0.00012813094],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99710035,0.000019442581,0.00049217494,0.00056389294,0.0016160153,0.00020813572],"domain_scores_gemma":[0.9964739,0.0011789858,0.00020830368,0.00053706876,0.0012934122,0.0003082914],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0059712897,0.000071313676,0.00012827349,0.00011124049,0.0004160064,0.0008782002,0.0024384614,0.00005599007,0.000036528578],"category_scores_gemma":[0.06993772,0.00006150133,0.00002207905,0.00016920528,0.0001756397,0.0038820354,0.001670235,0.00042406243,0.0000018813461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0042660157,0.0007919549,0.38512078,0.0010725043,0.000912276,0.00016457977,0.002460786,0.0011803362,0.122665815,0.16701096,0.056249063,0.25810495],"study_design_scores_gemma":[0.003685899,0.0003678534,0.023272729,0.00026744982,0.0001246638,0.00015276068,0.00029971692,0.9425203,0.0007599409,0.011607005,0.016713573,0.00022807853],"about_ca_topic_score_codex":0.00004805045,"about_ca_topic_score_gemma":0.000037633636,"teacher_disagreement_score":0.94133997,"about_ca_system_score_codex":0.00007030853,"about_ca_system_score_gemma":0.0004856642,"threshold_uncertainty_score":0.9378966},"labels":[],"label_agreement":null},{"id":"W3081563555","doi":"10.23889/ijpds.v5i1.1351","title":"Individual and neighbourhood socioeconomic status increase risk of avoidable hospitalizations among Canadian adults: A retrospective cohort study of linked population health data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; University of Toronto; University of Guelph","keywords":"Medicine; Socioeconomic status; Population; Neighbourhood (mathematics); Demography; Cohort; Household income; Environmental health; Gerontology; Geography","score_opus":0.05890006155872704,"score_gpt":0.4195591434814562,"score_spread":0.3606590819227291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081563555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98258746,0.000067685825,0.0004897522,0.002686078,0.0008759989,0.0015522763,0.011659511,0.000016598779,0.00006463595],"genre_scores_gemma":[0.99139154,0.0002288658,0.0012391302,0.0014225518,0.00026678975,0.000018330953,0.0054087597,0.000014918071,0.000009136706],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967108,0.00027801507,0.0012785923,0.00054367783,0.00077886047,0.00041010618],"domain_scores_gemma":[0.9958975,0.00024488728,0.001828465,0.00058556953,0.0008637116,0.00057986495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033296747,0.0001320436,0.00038811573,0.00043017356,0.0012725579,0.000072724346,0.001564949,0.00007315232,0.00012358505],"category_scores_gemma":[0.002861762,0.00012827491,0.00002805527,0.0003143929,0.00010896342,0.0026922626,0.0006927051,0.00041209953,0.0000023376797],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007139148,0.000061341794,0.99296474,0.0000359489,0.00008466434,6.4078625e-7,0.002535347,0.00009690479,0.0000010467536,0.0005295181,0.0024774903,0.0011409725],"study_design_scores_gemma":[0.0013904478,0.0002459418,0.97981644,0.00005822709,0.000056001503,0.0000013552246,0.0025846725,0.015021174,1.751252e-7,0.0004011925,0.00032159343,0.0001028056],"about_ca_topic_score_codex":0.5623971,"about_ca_topic_score_gemma":0.3849643,"teacher_disagreement_score":0.17743282,"about_ca_system_score_codex":0.001134094,"about_ca_system_score_gemma":0.003299856,"threshold_uncertainty_score":0.9787615},"labels":[],"label_agreement":null},{"id":"W3082148444","doi":"10.23889/ijpds.v5i1.1344","title":"Developing and validating a primary care EMR-based frailty definition using machine learning","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Frailty in Older Adults","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of British Columbia; University of Manitoba; Alberta Children's Hospital; University of Calgary","funders":"","keywords":"Medicine; Primary care; Medical record; Vulnerability (computing); Emergency medicine; Machine learning; Artificial intelligence; Internal medicine; Family medicine; Computer science","score_opus":0.24981096284793955,"score_gpt":0.41097682095276517,"score_spread":0.16116585810482562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082148444","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7637393,0.00017461361,0.2292774,0.0054443763,0.0006844322,0.0002785146,0.0002313023,0.00005808715,0.000111984555],"genre_scores_gemma":[0.7980198,0.000015136057,0.19881858,0.0012752609,0.0002978236,0.0000017151312,0.0015545043,0.000012176129,0.0000049827686],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983171,0.000027553353,0.00035616083,0.0003393031,0.0007859785,0.00017388568],"domain_scores_gemma":[0.99874157,0.00009335619,0.00025822737,0.00013495648,0.000610222,0.00016168442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004755096,0.00010443197,0.00013503862,0.0001933981,0.00044033714,0.0002754831,0.00044488613,0.000034142533,0.000016860839],"category_scores_gemma":[0.0019789548,0.00009952765,0.000031585452,0.0002423172,0.00008202139,0.0012999023,0.00023991831,0.00023805142,0.0000020934376],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063994364,0.00006560786,0.80175906,0.00049669953,0.00011172306,0.00009240112,0.0020923198,0.007354925,0.077237174,0.002625605,0.00013310568,0.10739143],"study_design_scores_gemma":[0.00356912,0.00024067877,0.12477223,0.0010408005,0.000094193754,0.00070123863,0.00050709175,0.86030126,0.0034405333,0.000559157,0.0044097146,0.0003639813],"about_ca_topic_score_codex":0.000092619615,"about_ca_topic_score_gemma":0.000014492091,"teacher_disagreement_score":0.85294634,"about_ca_system_score_codex":0.00034412794,"about_ca_system_score_gemma":0.00041927714,"threshold_uncertainty_score":0.40586197},"labels":[],"label_agreement":null},{"id":"W3090869181","doi":"10.23889/ijpds.v5i3.1364","title":"Public engagement can change your research, but how can it change your research institution? ICES Case Study","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Mental Health and Patient Involvement","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Public engagement; Public relations; Institution; Active listening; Public institution; Political science; Process (computing); Sociology; Business; Knowledge management; Computer science; Social science","score_opus":0.9662353567394159,"score_gpt":0.6775910938976282,"score_spread":0.2886442628417877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090869181","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8811197,0.000091979164,0.0002234959,0.10565291,0.0054721297,0.004909614,0.0021761656,0.00004340955,0.0003105579],"genre_scores_gemma":[0.9890434,0.0001353468,0.0004902661,0.004235933,0.0038622336,0.0007137271,0.0012100671,0.000019868503,0.000289164],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9912043,0.0015584118,0.00086929597,0.0008063061,0.0043551233,0.0012065468],"domain_scores_gemma":[0.99396217,0.00044448313,0.00048321197,0.0006125225,0.0034166547,0.0010809326],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01908782,0.00018545816,0.00021187092,0.0011141656,0.0075950553,0.0005288065,0.0027811718,0.00008340156,0.00018865823],"category_scores_gemma":[0.0026144753,0.00016031496,0.000042734686,0.0012976611,0.00027107098,0.003295981,0.0020071873,0.0015873213,0.000053890937],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036711342,0.0011370752,0.8221229,0.00042446255,0.000107074164,0.0009872159,0.09592176,0.000014115574,0.00013523287,0.00508639,0.038133204,0.035563495],"study_design_scores_gemma":[0.006857166,0.003689043,0.14679155,0.0013568059,0.000049825416,0.00036682063,0.43508655,0.024062492,0.000039728035,0.0011032593,0.37972358,0.00087319827],"about_ca_topic_score_codex":0.025572237,"about_ca_topic_score_gemma":0.016914764,"teacher_disagreement_score":0.6753313,"about_ca_system_score_codex":0.001593348,"about_ca_system_score_gemma":0.0014550876,"threshold_uncertainty_score":0.9936969},"labels":[],"label_agreement":null},{"id":"W3093793301","doi":"10.23889/ijpds.v6i1.1378","title":"The data we have: Pregnancy and birth related data collection in Australia, Canada, Europe and the USA- A web-based survey of practice","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Women's Health Research Institute","funders":"","keywords":"Medicine; Pregnancy; Live birth; Government (linguistics); Demography; High income countries; Environmental health; Family medicine; Developing country","score_opus":0.22540103832106845,"score_gpt":0.5217333727890584,"score_spread":0.29633233446798996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093793301","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88752913,0.0020172377,0.007334462,0.07131441,0.010192475,0.0029793833,0.017937845,0.000025341515,0.00066971016],"genre_scores_gemma":[0.9902161,0.0015766635,0.0028443672,0.000980376,0.00006179391,0.000010596599,0.0033908247,0.000006795682,0.0009125005],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.996176,0.001145315,0.0013421004,0.0003572808,0.0007585555,0.00022072518],"domain_scores_gemma":[0.99216294,0.003495217,0.0011692338,0.0012038121,0.0018704572,0.000098330216],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.016725425,0.00007894163,0.00013455101,0.00010463392,0.0012902113,0.00022127651,0.0022302454,0.000041945543,0.000046131965],"category_scores_gemma":[0.034521554,0.000048968726,0.000005949052,0.0006331692,0.00023855557,0.005684808,0.0012538311,0.00045514555,0.0000012189917],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005406259,0.00004905999,0.9700868,0.00008090561,0.000025333073,0.0000041970884,0.0005549472,0.00008896001,0.000009819663,0.0020390258,0.010814855,0.01570545],"study_design_scores_gemma":[0.0012738202,0.0000077686445,0.6588095,0.0002423641,0.000007115863,0.000021353864,0.0002047268,0.28220177,0.0000012855588,0.00014704504,0.05703615,0.00004709596],"about_ca_topic_score_codex":0.32241517,"about_ca_topic_score_gemma":0.7304579,"teacher_disagreement_score":0.40804276,"about_ca_system_score_codex":0.00014339751,"about_ca_system_score_gemma":0.004263096,"threshold_uncertainty_score":0.99233925},"labels":[],"label_agreement":null},{"id":"W3094191583","doi":"10.23889/ijpds.v5i1.1388","title":"Income inequalities in the risk of potentially avoidable hospitalisation for chronic obstructive pulmonary disease","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick; Saint John Regional Hospital","funders":"Canadian Institutes of Health Research; Dalhousie University; Diabetes Canada; Fondation de la recherche en santé du Nouveau-Brunswick","keywords":"COPD; Medicine; Odds ratio; Odds; Context (archaeology); Population; Demography; Ambulatory; Logistic regression; Gerontology; Environmental health; Internal medicine; Geography","score_opus":0.11697122577912708,"score_gpt":0.45254489076378135,"score_spread":0.33557366498465424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094191583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90039575,0.00031176565,0.05646673,0.029299393,0.0052319905,0.0022982445,0.0056920177,0.00002894991,0.0002751328],"genre_scores_gemma":[0.9934131,0.000086978114,0.0030863928,0.0018232551,0.00088661653,0.000064582564,0.0005954636,0.000007990633,0.000035631158],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99789166,0.00016864912,0.0007326223,0.0002469323,0.0007067276,0.00025338633],"domain_scores_gemma":[0.99752486,0.00077971467,0.0006827631,0.0002558678,0.00064176804,0.000115005794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025125982,0.00008515479,0.0001474744,0.00017947322,0.00073096727,0.000055199398,0.0015437719,0.000038230628,0.00004505913],"category_scores_gemma":[0.0032558518,0.000062251784,0.000060759776,0.00025867502,0.00009310748,0.0018829443,0.00024297358,0.00026770504,0.0000032411642],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006975611,0.000054037817,0.95238835,0.0002445047,0.000029717297,0.000004545989,0.0027927,0.0016248217,0.00012355525,0.027494686,0.0023898785,0.01215566],"study_design_scores_gemma":[0.00067312975,0.000066603534,0.9518772,0.0000693514,0.00002514009,0.000002118274,0.0011458378,0.018898781,0.0000041620606,0.020360846,0.006791781,0.00008508183],"about_ca_topic_score_codex":0.00048502407,"about_ca_topic_score_gemma":0.00026536218,"teacher_disagreement_score":0.09301731,"about_ca_system_score_codex":0.0004943361,"about_ca_system_score_gemma":0.0015650158,"threshold_uncertainty_score":0.5622083},"labels":[],"label_agreement":null},{"id":"W3107106297","doi":"10.23889/ijpds.v5i1.1374","title":"The SPOR-Canadian Data Platform: a national initiative to facilitate data rich multi-jurisdictional research","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; University of British Columbia; Canadian Institute for Health Information; Université de Sherbrooke; Sunnybrook Hospital; University Health Network; University of New Brunswick; University of Toronto; Laurentian University; Institute for Clinical Evaluative Sciences; Manitoba Health","funders":"Canadian Institutes of Health Research","keywords":"Jurisdiction; Health care; Research data; Public relations; Population; Political science; Medicine; Data science; Computer science; Environmental health; Data curation; Law","score_opus":0.8477296566595001,"score_gpt":0.6540354937349164,"score_spread":0.19369416292458363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107106297","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047701824,0.00018927637,0.036039792,0.796338,0.023249732,0.0038153434,0.0873806,0.0001170147,0.005168369],"genre_scores_gemma":[0.880255,0.00036524053,0.023765195,0.036539055,0.01299536,0.00018124847,0.044000853,0.000058663747,0.0018394232],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99400884,0.00031508936,0.0010174015,0.00086891034,0.002793363,0.0009963808],"domain_scores_gemma":[0.9905681,0.0017541641,0.00039820228,0.0014624649,0.004574513,0.0012425348],"candidate_categories":["metaresearch","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.019071164,0.00014506494,0.00015000858,0.00063886726,0.006867431,0.00053517875,0.011138918,0.00009303077,0.00021435795],"category_scores_gemma":[0.024917632,0.00011348363,0.000020712656,0.0012601732,0.00026140403,0.0062832977,0.0035828268,0.0010098923,0.000393444],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014783503,0.000050176834,0.013988588,0.000017119928,0.000051716503,0.00000238033,0.004287124,0.00024221692,0.000027789274,0.015572946,0.9549725,0.010639624],"study_design_scores_gemma":[0.00043515032,0.00003851256,0.06857409,0.000044968125,0.000004521799,0.000010234729,0.0028038346,0.13115318,5.055631e-7,0.0018874176,0.79493177,0.00011581302],"about_ca_topic_score_codex":0.02435611,"about_ca_topic_score_gemma":0.040672597,"teacher_disagreement_score":0.83255315,"about_ca_system_score_codex":0.0012605275,"about_ca_system_score_gemma":0.011447209,"threshold_uncertainty_score":0.9944255},"labels":[],"label_agreement":null},{"id":"W3107592974","doi":"10.23889/ijpds.v5i3.1369","title":"Impact through Engagement","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Economic and Social Research Council; Queen's University; Ulster University; Queen's University Belfast; Health and Social Care Northern Ireland; UK Research and Innovation","keywords":"Public engagement; General partnership; Publics; Public relations; Work (physics); Key (lock); Community engagement; Business; Political science; Knowledge management; Computer science; Engineering","score_opus":0.5733097696198401,"score_gpt":0.5698511322761074,"score_spread":0.003458637343732751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107592974","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35711288,0.000047299858,0.62598556,0.011875309,0.0035004332,0.0001978979,0.00042718215,0.000044996777,0.0008084681],"genre_scores_gemma":[0.98117626,0.00003629689,0.01701493,0.0010257771,0.0005309057,0.0000024029396,0.00015988699,0.0000064564133,0.000047095316],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99533904,0.00006745777,0.00071285124,0.0005415028,0.0031211877,0.00021798338],"domain_scores_gemma":[0.9971684,0.00031131934,0.00046390932,0.00046014495,0.0014012511,0.00019493252],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0050960863,0.000099720404,0.00012940049,0.00025769018,0.0005261045,0.0015579605,0.004199477,0.000025819018,0.00028291604],"category_scores_gemma":[0.008333358,0.00007062548,0.00010501034,0.00081363483,0.00009902214,0.005203754,0.0004431965,0.00015228054,0.0000754911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006476931,0.00026633748,0.24264137,0.0000057789025,0.00020030954,0.000027786655,0.0042844396,0.10635743,0.0054880846,0.056993727,0.10664063,0.47644642],"study_design_scores_gemma":[0.00075428066,0.00015701156,0.096990615,0.000016007869,0.000017131188,0.000051050953,0.00066214835,0.7754239,0.000050005692,0.05863683,0.06702655,0.00021445449],"about_ca_topic_score_codex":0.00006152542,"about_ca_topic_score_gemma":0.0000086242635,"teacher_disagreement_score":0.6690665,"about_ca_system_score_codex":0.00007320975,"about_ca_system_score_gemma":0.000176662,"threshold_uncertainty_score":0.9994785},"labels":[],"label_agreement":null},{"id":"W3110853613","doi":"10.23889/ijpds.v5i5.1556","title":"Using the Canadian Institute for Health Information’s Information Quality Framework to Support Integration and Utilization of Complex, Multi-Jurisdictional Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Data quality; Information quality; Computer science; Documentation; Operationalization; Data science; Health informatics; Quality (philosophy); Information system; Data governance; Health care; Knowledge management; Business; Engineering","score_opus":0.7470190652398002,"score_gpt":0.5982658809769009,"score_spread":0.1487531842628993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110853613","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023746141,0.000004835911,0.94617546,0.035328534,0.0014747399,0.0007024721,0.013902892,0.000010853793,0.000025598374],"genre_scores_gemma":[0.7562675,0.000015962038,0.21678853,0.01183522,0.000228413,0.000010085922,0.014842822,0.000004274627,0.000007203408],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959131,0.00009819821,0.0014868075,0.0003222698,0.0019652543,0.00021436777],"domain_scores_gemma":[0.99555415,0.00031189213,0.0011158556,0.00074069697,0.0019522525,0.00032512977],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.010899685,0.00010847796,0.00017987181,0.0005869973,0.0011158132,0.001818835,0.0038506873,0.000043103963,0.000036888432],"category_scores_gemma":[0.016317794,0.00008216475,0.00003383815,0.00077708444,0.00018844237,0.019475495,0.00088411133,0.00012967679,0.000007710297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035966022,0.00006406775,0.008643672,0.000053382253,0.00007589806,2.7286657e-7,0.0076567093,0.01982592,0.00006454362,0.34678388,0.07204919,0.5444228],"study_design_scores_gemma":[0.000447135,0.0000800032,0.053987626,0.000030528303,0.000010887352,0.000009057008,0.0011615081,0.58153456,0.000009537071,0.0068732314,0.35573602,0.00011993319],"about_ca_topic_score_codex":0.013518417,"about_ca_topic_score_gemma":0.04181983,"teacher_disagreement_score":0.7538929,"about_ca_system_score_codex":0.0002597967,"about_ca_system_score_gemma":0.0011104281,"threshold_uncertainty_score":0.9992174},"labels":[],"label_agreement":null},{"id":"W3110889581","doi":"10.23889/ijpds.v5i5.1521","title":"Association Between Active Living Environments and Hospitalization for All-Causes and Cardiometabolic Disease","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada; McGill University","funders":"","keywords":"Medicine; Logistic regression; Odds; Demography; Neighbourhood (mathematics); Active living; Population; Activities of daily living; Gerontology; Binomial regression; Environmental health; Physical activity; Physical therapy","score_opus":0.09109446460401804,"score_gpt":0.41833056381709144,"score_spread":0.3272360992130734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110889581","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9226965,0.00025889842,0.036627542,0.036113776,0.0018303256,0.00073358626,0.0016583898,0.000027325197,0.000053700667],"genre_scores_gemma":[0.9958474,0.00066192483,0.0012601156,0.0010858538,0.00092113606,0.000009101322,0.00014706612,0.000005869205,0.00006151484],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986329,0.000040322677,0.00021418548,0.00023869005,0.0006636686,0.00021022011],"domain_scores_gemma":[0.998857,0.00039294787,0.00022606099,0.00006689456,0.00013533655,0.000321727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011450407,0.000061073915,0.000100777295,0.00008971536,0.0007360242,0.00045641695,0.00040243554,0.000030924206,0.000009799878],"category_scores_gemma":[0.0055532246,0.00006119131,0.000023918497,0.00011128196,0.00008509515,0.0024080123,0.00014566307,0.000052508338,6.9099866e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022007447,0.000008725746,0.97382146,0.000011932416,0.000058463636,2.795075e-7,0.0014776739,0.000038311977,0.000009943366,0.005815025,0.00058053876,0.018155638],"study_design_scores_gemma":[0.00020938879,0.00001330961,0.9337678,0.000024793344,0.000052072013,2.7943105e-7,0.00043802464,0.0023040231,0.0000030561816,0.0012330178,0.06187543,0.00007879836],"about_ca_topic_score_codex":0.00034022474,"about_ca_topic_score_gemma":0.00008867029,"teacher_disagreement_score":0.07315096,"about_ca_system_score_codex":0.00020229544,"about_ca_system_score_gemma":0.00012464226,"threshold_uncertainty_score":0.664813},"labels":[],"label_agreement":null},{"id":"W3110904644","doi":"10.23889/ijpds.v5i5.1483","title":"The New Brunswick Act Respecting Research Three Years Later: A Data Trickle Turns into a Flood","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Legislation; Attendance; Government (linguistics); Public administration; Political science; Law","score_opus":0.6274357652473137,"score_gpt":0.6171628963456305,"score_spread":0.010272868901683219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110904644","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5184635,0.000420631,0.049234647,0.42458248,0.0051470734,0.001565584,0.0002764809,0.00009681678,0.00021276613],"genre_scores_gemma":[0.970309,0.00016613082,0.023688372,0.0013901952,0.003486762,0.0000020890823,0.0008141782,0.000019547337,0.0001237064],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957897,0.00009747069,0.00095772813,0.0005738047,0.0022616296,0.0003196757],"domain_scores_gemma":[0.995314,0.0017143204,0.00045484843,0.0009898806,0.0011578484,0.0003690847],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.009720466,0.00009325157,0.00013636482,0.00022158657,0.00060927693,0.00090417376,0.0036089183,0.000039631843,0.000070923634],"category_scores_gemma":[0.04908049,0.00007011853,0.000045518787,0.00076056586,0.0001597811,0.0033329262,0.0017457798,0.00060908403,0.000045303346],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034177923,0.00017688236,0.1499977,0.000029401288,0.0003576507,0.00011087297,0.002102299,0.00028719628,0.0042918464,0.0046583596,0.1435218,0.6910482],"study_design_scores_gemma":[0.0042270804,0.0004972699,0.27918229,0.00012526974,0.00013066236,0.00041723397,0.0011909801,0.23183405,0.000108713844,0.010532827,0.47152328,0.00023033096],"about_ca_topic_score_codex":0.0022650848,"about_ca_topic_score_gemma":0.004714188,"teacher_disagreement_score":0.6908179,"about_ca_system_score_codex":0.0002301652,"about_ca_system_score_gemma":0.0025360659,"threshold_uncertainty_score":0.9589295},"labels":[],"label_agreement":null},{"id":"W3110913174","doi":"10.23889/ijpds.v5i5.1515","title":"Collaboration with First Nations Communities to Produce Tailored Community-Driven Results","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Indigenous; Government (linguistics); Public relations; Population; Population health; Community health; Dissemination; Political science; Business; Economic growth; Health care; Medicine; Environmental health","score_opus":0.599999049100667,"score_gpt":0.5937240744897508,"score_spread":0.006274974610916195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110913174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48716098,0.000018162276,0.027479295,0.4782921,0.001393653,0.0017307225,0.0018472486,0.000107972446,0.001969851],"genre_scores_gemma":[0.96766496,0.000068398345,0.028059974,0.0020888261,0.00045590932,0.00001864418,0.001436394,0.000013764634,0.0001931286],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.996721,0.00010717396,0.0005671394,0.00027197422,0.0021265517,0.00020614464],"domain_scores_gemma":[0.988632,0.0040387195,0.000299785,0.0008658514,0.0057410668,0.00042255173],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.0041730157,0.0001001685,0.00015183167,0.00039716123,0.0016689176,0.00061038544,0.0023993826,0.000060794064,0.00002275779],"category_scores_gemma":[0.059834264,0.00008277499,0.00002777922,0.0011273279,0.00033237343,0.0017415421,0.0007046916,0.001034537,0.000019545321],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.037447017,0.0037688522,0.35332277,0.0012480078,0.001254315,0.00020659626,0.09413647,0.11484443,0.0156212365,0.23182496,0.13221054,0.0141148055],"study_design_scores_gemma":[0.019400261,0.010039764,0.41087306,0.005038996,0.00026912516,0.00085959985,0.034148064,0.2674032,0.003198249,0.011755866,0.23554336,0.0014704656],"about_ca_topic_score_codex":0.00041820653,"about_ca_topic_score_gemma":0.016774517,"teacher_disagreement_score":0.48050398,"about_ca_system_score_codex":0.00024375987,"about_ca_system_score_gemma":0.0011667426,"threshold_uncertainty_score":0.99963075},"labels":[],"label_agreement":null},{"id":"W3110954960","doi":"10.23889/ijpds.v5i5.1645","title":"Changing Practice Patterns Among Canadian Primary Care Physicians: Cross-Provincial Analysis of Linked Health Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Dalhousie University; University of Ottawa; University of British Columbia; Ontario Tech University; Simon Fraser University","funders":"","keywords":"Family medicine; Medicine; Cohort; Primary care; Service (business); Population; Per capita; Health care; Business; Environmental health","score_opus":0.16579242576322498,"score_gpt":0.5209681174331734,"score_spread":0.35517569166994845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110954960","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70797956,0.0008091304,0.06768711,0.10749861,0.017880872,0.0031938625,0.09226037,0.00016282286,0.0025276623],"genre_scores_gemma":[0.9417136,0.00012371603,0.0032583734,0.03390115,0.0014967696,0.000009225276,0.019433698,0.000017380868,0.00004613651],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99635816,0.00017932613,0.0010772593,0.0005861667,0.0011832664,0.0006158385],"domain_scores_gemma":[0.995282,0.0003759684,0.0014023896,0.0008159914,0.0016477467,0.0004759048],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002901486,0.00013482271,0.0003780255,0.0009629656,0.0016379762,0.0001489105,0.0036571107,0.00007494508,0.0000846847],"category_scores_gemma":[0.0023848081,0.0001311701,0.00007983603,0.0012227912,0.00010215989,0.0050140074,0.0011327185,0.00048616063,0.0000071416125],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011925464,0.000025922924,0.94897527,0.00020063051,0.00027384819,0.000009806487,0.0059854724,0.00045731373,0.000019462535,0.0005545275,0.0041467072,0.039231762],"study_design_scores_gemma":[0.0005400984,0.000053089043,0.938346,0.00012312729,0.00016414202,0.0000023737796,0.0033267706,0.023665983,0.0000013142031,0.000022793733,0.033604514,0.00014978973],"about_ca_topic_score_codex":0.091317534,"about_ca_topic_score_gemma":0.15907422,"teacher_disagreement_score":0.23373398,"about_ca_system_score_codex":0.0018054154,"about_ca_system_score_gemma":0.0068803458,"threshold_uncertainty_score":0.99966174},"labels":[],"label_agreement":null},{"id":"W3110957447","doi":"10.23889/ijpds.v5i5.1565","title":"Exploring the Collection and Use of Health Data for Smart Cities Initiatives","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Enabling; Stakeholder; Business; Open data; Corporate governance; Data sharing; Smart city; Data collection; Public relations; Computer security; Public administration; Computer science; Political science; Medicine; Sociology; World Wide Web","score_opus":0.7606411700335738,"score_gpt":0.5871003982914391,"score_spread":0.17354077174213467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110957447","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6314435,0.0001389659,0.084196836,0.2649743,0.012226612,0.001967733,0.004921052,0.000040498977,0.00009047772],"genre_scores_gemma":[0.98006403,0.0007807361,0.008896426,0.006943699,0.001631829,0.00008094217,0.0015024286,0.000012405215,0.00008749029],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9983342,0.00014669765,0.00064757885,0.00023664355,0.0003943852,0.00024044937],"domain_scores_gemma":[0.9972941,0.0009529223,0.0006315609,0.00032217737,0.0006645849,0.00013461421],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0035124086,0.00006105806,0.00012357523,0.00014552369,0.0017657768,0.00011690268,0.0010666961,0.000018577799,0.000011282225],"category_scores_gemma":[0.006540096,0.00004523058,0.000014407501,0.00027012167,0.00011365238,0.00553852,0.0004656698,0.00016130974,8.382446e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067883247,0.00014894412,0.3343919,0.0007314179,0.00016618689,3.3617397e-7,0.057068307,0.00047233835,0.00028883576,0.109427,0.37617403,0.120451875],"study_design_scores_gemma":[0.0006077571,0.0001331108,0.55445033,0.00016751498,0.0000106782945,0.0000061673886,0.008516003,0.086757086,0.000006030198,0.0012426578,0.3480073,0.000095343465],"about_ca_topic_score_codex":0.0019346891,"about_ca_topic_score_gemma":0.0002120567,"teacher_disagreement_score":0.34862053,"about_ca_system_score_codex":0.00013262384,"about_ca_system_score_gemma":0.0010967264,"threshold_uncertainty_score":0.9995338},"labels":[],"label_agreement":null},{"id":"W3111051924","doi":"10.23889/ijpds.v5i5.1593","title":"Time-Varying Vulnerability to Non-Fatal Overdose: A Self-Controlled Case Series","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"BC Centre for Disease Control","funders":"","keywords":"Medicine; Emergency department; Rate ratio; Poisson regression; Emergency medicine; Incidence (geometry); Confidence interval; Drug overdose; Relative risk; Confounding; Poison control; Medical prescription; Internal medicine; Psychiatry; Population; Environmental health; Pharmacology","score_opus":0.04055713621111789,"score_gpt":0.37402007726589015,"score_spread":0.33346294105477226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111051924","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9792814,0.000028605422,0.005221759,0.012738581,0.0010004658,0.0009960461,0.0004777146,0.00006457346,0.00019085316],"genre_scores_gemma":[0.97681946,0.000008631656,0.020918239,0.001164181,0.00053681794,0.000022996064,0.00038905148,0.00001352888,0.00012707427],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979458,0.000023512901,0.000467613,0.00046265102,0.0008738087,0.00022660906],"domain_scores_gemma":[0.9984309,0.00007442518,0.00017951723,0.00035457217,0.0005799625,0.00038060214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068776234,0.00013939416,0.00025065077,0.00018537483,0.000351164,0.00025384608,0.00067509373,0.000029880232,0.00011203692],"category_scores_gemma":[0.0017330024,0.00011444251,0.000083657695,0.0003213774,0.000059927774,0.0018751778,0.0003241339,0.00014034091,0.00004594678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.058910217,0.0074006924,0.5445409,0.0006543562,0.004770528,0.017572062,0.038782515,0.02867401,0.11560734,0.0040302905,0.052529883,0.12652722],"study_design_scores_gemma":[0.03943269,0.0026023616,0.09334486,0.00035687277,0.0005583752,0.032128613,0.0014007671,0.8008338,0.00290626,0.0006968772,0.024658484,0.001080006],"about_ca_topic_score_codex":0.000095780415,"about_ca_topic_score_gemma":0.000012533014,"teacher_disagreement_score":0.7721598,"about_ca_system_score_codex":0.00028027938,"about_ca_system_score_gemma":0.00034047663,"threshold_uncertainty_score":0.466683},"labels":[],"label_agreement":null},{"id":"W3111116118","doi":"10.23889/ijpds.v5i5.1470","title":"Risk of Overdose-Related Death for People with A History of Incarceration","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"BC Centre for Disease Control","funders":"","keywords":"Medicine; Drug overdose; Demography; Cohort; Medical examiner; Cohort study; Confidence interval; Population; Poison control; Injury prevention; Emergency medicine; Environmental health; Internal medicine","score_opus":0.04913606485236244,"score_gpt":0.34313966034040566,"score_spread":0.2940035954880432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111116118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95799756,0.00018477529,0.037714794,0.0017427073,0.00056567224,0.000708179,0.00077076186,0.000015577129,0.00029995127],"genre_scores_gemma":[0.9856425,0.00004606322,0.013351767,0.00008429386,0.000081192586,0.000007905701,0.0006678016,0.00000768927,0.0001107687],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987134,0.000011936436,0.0003741734,0.00020379778,0.00060793175,0.000088801535],"domain_scores_gemma":[0.9983867,0.00006053922,0.0004943433,0.00018306759,0.00079072267,0.000084636595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003467486,0.00006913363,0.00015766633,0.0001535431,0.00005502582,0.000016484593,0.00037558723,0.000022595244,0.00003018569],"category_scores_gemma":[0.00074717466,0.000054188942,0.000049911498,0.00014642022,0.000060647402,0.00067318196,0.0000600717,0.00006449245,6.639807e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002566137,0.00046835444,0.95711315,0.000136244,0.0004558196,0.0000036250622,0.0035009033,0.0037684254,0.009486362,0.007972372,0.005057772,0.009470809],"study_design_scores_gemma":[0.0045275157,0.0010455129,0.6854504,0.000119208,0.00027900742,0.00005264176,0.00017477441,0.3033431,0.00090261054,0.0007161398,0.0032772499,0.000111880814],"about_ca_topic_score_codex":0.00018518053,"about_ca_topic_score_gemma":0.000028948534,"teacher_disagreement_score":0.29957464,"about_ca_system_score_codex":0.00029197705,"about_ca_system_score_gemma":0.00052284193,"threshold_uncertainty_score":0.22097608},"labels":[],"label_agreement":null},{"id":"W3111190599","doi":"10.23889/ijpds.v5i5.1477","title":"British Columbia’s Health Data Platform: Unleashing the Power of a Data Environment Commons for Health and Health System Improvement","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ministry of Health","funders":"Economic and Social Research Council","keywords":"Transparency (behavior); Data governance; Data quality; Data sharing; Information privacy; Data security; Data management; Agile software development; Computer science; Business; Data science; Computer security; Database; Medicine; Marketing","score_opus":0.2740117676628542,"score_gpt":0.49170335932663833,"score_spread":0.21769159166378416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111190599","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020744488,0.0036479088,0.14287376,0.7409715,0.006503094,0.008141068,0.076893315,0.000112548594,0.00011229222],"genre_scores_gemma":[0.79888797,0.0028575652,0.0377617,0.13115,0.0016082473,0.00009945295,0.02736836,0.000068854046,0.00019784801],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9956494,0.0001679354,0.0017025125,0.0007496843,0.0011032398,0.0006272523],"domain_scores_gemma":[0.99534094,0.00040711835,0.0019437287,0.0014619384,0.00023499258,0.0006112954],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.009781666,0.00012479964,0.00042934137,0.00008015724,0.0025078563,0.00032202862,0.0050462843,0.000046266225,0.00005682974],"category_scores_gemma":[0.00068631297,0.00012501149,0.00003358732,0.00016575053,0.00013799327,0.0028837821,0.0036034815,0.00042973846,0.0000023342614],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013458211,0.00008991669,0.051688246,0.0009919873,0.00008828298,0.0000016832382,0.0021019278,0.000026003396,0.000010648374,0.0021166557,0.8052578,0.13749225],"study_design_scores_gemma":[0.0038590205,0.0012158051,0.13428771,0.0011744795,0.000029899911,0.00010041866,0.009912297,0.06853951,3.869529e-7,0.00061039644,0.779916,0.0003540945],"about_ca_topic_score_codex":0.03245697,"about_ca_topic_score_gemma":0.028282613,"teacher_disagreement_score":0.77814347,"about_ca_system_score_codex":0.0012282698,"about_ca_system_score_gemma":0.005413152,"threshold_uncertainty_score":0.99879074},"labels":[],"label_agreement":null},{"id":"W3111253075","doi":"10.23889/ijpds.v5i5.1606","title":"High Rate of Fatal Overdose After Release from Prison In BC, Canada: A Data Linkage Study","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"BC Centre for Disease Control","funders":"","keywords":"Medicine; Drug overdose; Prison; Population; Incidence (geometry); Cohort; Opioid overdose; Cause of death; Cohort study; Mortality rate; Poison control; Demography; Emergency medicine; Internal medicine; Opioid; Environmental health; Psychology; Disease","score_opus":0.06038386284692541,"score_gpt":0.3626157600295581,"score_spread":0.30223189718263266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111253075","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98917854,0.00007265646,0.0009844486,0.004496727,0.00074629916,0.00043183344,0.0040778928,0.0000069169637,0.0000047083213],"genre_scores_gemma":[0.99219465,0.00002407365,0.0034873649,0.0004987424,0.00022281578,0.000006506689,0.0035420419,0.00000964294,0.000014158651],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979224,0.000040718027,0.0005356347,0.00047469142,0.00087450404,0.00015202866],"domain_scores_gemma":[0.9986033,0.000073110925,0.00026047893,0.0006420751,0.00025192983,0.00016913105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051520695,0.00010724335,0.00019411145,0.0001379131,0.000056695237,0.00008038324,0.0014039122,0.000018383746,0.00008474246],"category_scores_gemma":[0.0011530627,0.000092177645,0.000020184294,0.00026037265,0.000041488274,0.0012735357,0.0006474035,0.00015366636,0.0000030406404],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015872798,0.0007842987,0.9845539,0.000019203506,0.00014752462,0.00043216758,0.0008096678,0.0004719031,0.0009212221,0.000082009894,0.0023473455,0.007843526],"study_design_scores_gemma":[0.0030102737,0.00019129243,0.95944726,0.000086706954,0.000059805447,0.000008798873,0.00039688702,0.035285432,0.00018897784,0.00007344721,0.001157918,0.00009317718],"about_ca_topic_score_codex":0.29215974,"about_ca_topic_score_gemma":0.10526126,"teacher_disagreement_score":0.18689848,"about_ca_system_score_codex":0.00027137232,"about_ca_system_score_gemma":0.0009858673,"threshold_uncertainty_score":0.9110654},"labels":[],"label_agreement":null},{"id":"W3111257782","doi":"10.23889/ijpds.v5i5.1542","title":"Evaluating PPRL Vs Clear Text Linkage with Real-World Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Linkage (software); Identifier; Genetic linkage; Computer science; Record linkage; Population; Hash function; Genetics; Biology; Gene; Medicine","score_opus":0.6781494335367946,"score_gpt":0.5956232882520471,"score_spread":0.08252614528474744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111257782","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22053093,0.000058493475,0.61741745,0.13417552,0.009065728,0.0015861957,0.010689627,0.00022736598,0.0062486785],"genre_scores_gemma":[0.89047265,0.000048910177,0.10118659,0.0036471733,0.001349901,0.000004667953,0.0024079892,0.000019081654,0.0008630148],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99222904,0.00015795705,0.000979,0.0011282427,0.0052021947,0.00030356034],"domain_scores_gemma":[0.9950277,0.0006903172,0.0009484146,0.0018951378,0.0011401039,0.0002982885],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.015254593,0.0001426015,0.00021705539,0.0004723427,0.00064017985,0.0030113002,0.014319866,0.000019732892,0.0002687066],"category_scores_gemma":[0.013013974,0.00010310984,0.000038492784,0.0014287152,0.00028332983,0.00974243,0.003914248,0.00022820961,0.00017284672],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021040763,0.00019235814,0.03925466,0.000017221846,0.00014639141,0.000053212654,0.000814227,0.00986361,0.0005750745,0.05210825,0.14764215,0.74722874],"study_design_scores_gemma":[0.0011130085,0.00044430664,0.06025486,0.00006856714,0.000042901516,0.000035497604,0.00070104335,0.51164925,0.000056756893,0.0068425187,0.4184654,0.00032590728],"about_ca_topic_score_codex":0.00036500295,"about_ca_topic_score_gemma":0.00092852104,"teacher_disagreement_score":0.7469028,"about_ca_system_score_codex":0.00009872331,"about_ca_system_score_gemma":0.00028034518,"threshold_uncertainty_score":0.9980237},"labels":[],"label_agreement":null},{"id":"W3111282224","doi":"10.23889/ijpds.v5i5.1524","title":"The Role of Partnership in The Integration of Intersectoral Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Public Health Policies and Epidemiology","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Health Information; University of New Brunswick","funders":"","keywords":"General partnership; Data sharing; Business; Legislature; Public relations; Data governance; Knowledge management; Best practice; Political science; Computer science; Data quality; Marketing; Medicine","score_opus":0.2538097090373604,"score_gpt":0.4425573073661793,"score_spread":0.18874759832881893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111282224","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6358738,0.00030507008,0.009857429,0.3432874,0.0044195317,0.0008744356,0.00044130537,0.000027721706,0.0049132803],"genre_scores_gemma":[0.9949693,0.000014426199,0.00024400163,0.003783097,0.00071478717,0.00000162289,0.00026828118,0.0000023400848,0.0000021266035],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987637,0.000028278999,0.0004847779,0.00015426539,0.000420056,0.00014896817],"domain_scores_gemma":[0.99861944,0.00019456948,0.0005013542,0.00034002596,0.0003308793,0.000013739626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037435368,0.00004927371,0.000087255634,0.0001026543,0.00015250743,0.0002090662,0.0038295574,0.000017564342,0.000009041142],"category_scores_gemma":[0.00528922,0.000027871027,0.000021256825,0.00036586978,0.00014088076,0.0025776583,0.00056397,0.00010556976,0.0000024075123],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025604366,0.00007220364,0.09505065,0.00003174051,0.000026464497,0.0000010848969,0.00049840653,0.001817481,0.0009413608,0.72045785,0.117365725,0.063480996],"study_design_scores_gemma":[0.00019628262,0.000015709438,0.04887435,0.000024760839,0.000006665391,0.0000034371876,0.0016881155,0.47988865,0.0000072899293,0.01008761,0.45916215,0.000044996672],"about_ca_topic_score_codex":0.0032430284,"about_ca_topic_score_gemma":0.0006541446,"teacher_disagreement_score":0.71037024,"about_ca_system_score_codex":0.000020872136,"about_ca_system_score_gemma":0.000061341525,"threshold_uncertainty_score":0.71163344},"labels":[],"label_agreement":null},{"id":"W3111388631","doi":"10.23889/ijpds.v5i5.1423","title":"Participation in Boys &amp; Girls Clubs Of Winnipeg is Associated With Health, Social and Education Outcomes Among First Nation Children","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; First Nations Health and Social Secretariat of Manitoba; Manitoba Health","funders":"","keywords":"Socioeconomic status; Attendance; Population; Psychology; Gerontology; Medicine; Demography; Sociology; Political science","score_opus":0.20505101189239172,"score_gpt":0.508378711479442,"score_spread":0.3033276995870503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111388631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99019337,0.000023928758,0.0010568518,0.007431246,0.00047725686,0.00047628954,0.0002878331,0.000015059937,0.000038155616],"genre_scores_gemma":[0.99781793,0.000027511538,0.0004418958,0.00055480207,0.00026825545,0.000026138887,0.00080349686,0.000009814073,0.000050169052],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99801487,0.00012166729,0.0006710786,0.0002632579,0.00070514315,0.00022397075],"domain_scores_gemma":[0.99805486,0.00014501411,0.0008604907,0.000106330735,0.0007114073,0.00012192159],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012711503,0.00009423702,0.0002588444,0.00021363777,0.0008229083,0.00007444782,0.0004849637,0.00007032033,0.000036095917],"category_scores_gemma":[0.0013137746,0.00008177103,0.000024874482,0.00038310845,0.000115226874,0.0016060967,0.00012263951,0.00021449925,0.0000021893395],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000358591,0.00006828349,0.9835635,0.00001579845,0.000020709811,9.148331e-8,0.011135926,0.000031420353,0.0000110141855,0.001061684,0.00025709908,0.003798651],"study_design_scores_gemma":[0.000681163,0.000035744655,0.9952218,0.00011029198,0.000008984759,1.6405582e-7,0.0017436318,0.0015089918,0.0000061272726,0.000413363,0.0001864485,0.00008327497],"about_ca_topic_score_codex":0.0031889728,"about_ca_topic_score_gemma":0.015625846,"teacher_disagreement_score":0.012436872,"about_ca_system_score_codex":0.00026304918,"about_ca_system_score_gemma":0.0005190936,"threshold_uncertainty_score":0.87195885},"labels":[],"label_agreement":null},{"id":"W3111411783","doi":"10.23889/ijpds.v5i5.1637","title":"Deep Learning and NLP For Knowledge Extraction from Laboratory Reports","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Vector Institute; University of Toronto","funders":"","keywords":"Computer science; Artificial intelligence; Identifier; Natural language processing; Named-entity recognition; Parsing; Information extraction; Information retrieval; F1 score; Deep learning; Identification (biology); ENCODE; Task (project management); Machine learning","score_opus":0.056942037700102754,"score_gpt":0.3996541144822478,"score_spread":0.34271207678214505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111411783","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6340051,0.0014143233,0.35904938,0.0023946234,0.0026637786,0.00017110797,0.00021599646,0.000025395671,0.000060259765],"genre_scores_gemma":[0.9754405,0.00010452986,0.022514962,0.00018117568,0.000981213,0.0000045671745,0.0007248207,0.0000057528605,0.000042498123],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99923915,0.000014831087,0.0001901362,0.0002894059,0.00017184163,0.00009463413],"domain_scores_gemma":[0.9993221,0.000047084308,0.00016392539,0.00009259525,0.000280133,0.00009414079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045723672,0.000053962533,0.000057181285,0.000037308655,0.0001969225,0.00012224638,0.0003084708,0.000048344227,0.00000692],"category_scores_gemma":[0.002931899,0.00004863757,0.00002026386,0.000058795016,0.000087095344,0.00004848188,0.0001512586,0.00007187476,7.0256385e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034606957,0.0000688136,0.05723875,0.000016309858,0.00009917764,0.000012941831,0.00034786694,0.00028585998,0.50169086,0.00026220907,0.008623272,0.43100783],"study_design_scores_gemma":[0.0006870447,0.0002945171,0.030176628,0.000027286376,0.000024428116,0.00009492485,0.0003361513,0.056892503,0.00918052,0.0007609674,0.90131825,0.00020679533],"about_ca_topic_score_codex":0.00000962652,"about_ca_topic_score_gemma":0.000015057041,"teacher_disagreement_score":0.89269495,"about_ca_system_score_codex":0.000014466158,"about_ca_system_score_gemma":0.00007189826,"threshold_uncertainty_score":0.35099685},"labels":[],"label_agreement":null},{"id":"W3111412015","doi":"10.23889/ijpds.v5i5.1450","title":"Using Linked Administrative Health Databases for An Obesity Case Definition","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Promotion and Cardiovascular Prevention","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Medicine; Medical prescription; Obesity; Body mass index; Diagnosis code; Population; Health care; Database; Family medicine; Pediatrics; Environmental health; Internal medicine; Computer science","score_opus":0.6411845115247103,"score_gpt":0.5615565348109857,"score_spread":0.07962797671372468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111412015","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18193921,0.000047505247,0.81087387,0.004141538,0.00089345063,0.00081957376,0.0012268161,0.00003145698,0.000026560932],"genre_scores_gemma":[0.88692755,0.000030329113,0.107528016,0.0015749218,0.00082749093,0.00000634217,0.0030900526,0.000009331498,0.0000059463528],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99822223,0.00014289566,0.00046396654,0.0003675475,0.00060980534,0.0001935394],"domain_scores_gemma":[0.99821794,0.000045880824,0.0003106271,0.00025386363,0.00074809516,0.0004235943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035642697,0.000085800006,0.0001682073,0.00013693882,0.0005967477,0.00013569467,0.0003227326,0.000026979715,0.00002591262],"category_scores_gemma":[0.0013185194,0.00008147395,0.00009062695,0.00018553375,0.00005928197,0.0020830492,0.00008293276,0.0001321264,0.0000024413328],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024513437,0.0028209472,0.039647907,0.0013975397,0.000921348,0.0010227001,0.004756072,0.0023359451,0.011724585,0.060825206,0.007907715,0.8641887],"study_design_scores_gemma":[0.0097325845,0.003111454,0.071965344,0.00068677356,0.00032776533,0.024644878,0.0023006864,0.85027593,0.0005232457,0.00357937,0.03221326,0.00063871505],"about_ca_topic_score_codex":0.00014555035,"about_ca_topic_score_gemma":0.00006613918,"teacher_disagreement_score":0.86355,"about_ca_system_score_codex":0.00021509049,"about_ca_system_score_gemma":0.000805655,"threshold_uncertainty_score":0.45897612},"labels":[],"label_agreement":null},{"id":"W3111439089","doi":"10.23889/ijpds.v5i5.1559","title":"Identification of Determinants of Resilience in Children Using Administrative Health, Social, Justice and Education Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Resilience and Mental Health","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Psychological resilience; Psychology; Mental health; Population; Economic Justice; Context (archaeology); Medicine; Psychiatry; Political science; Social psychology; Environmental health; Geography","score_opus":0.23819363282875386,"score_gpt":0.5740861082791133,"score_spread":0.3358924754503595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111439089","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99497205,0.00014147877,0.0023949326,0.00083675055,0.0007403367,0.00026947304,0.00062307285,0.000002539686,0.0000193681],"genre_scores_gemma":[0.9977764,0.000062131716,0.0016121849,0.00019221916,0.00014469444,0.0000019648069,0.00019617303,0.000003627106,0.000010611583],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983266,0.00005932268,0.00071121386,0.00034697202,0.00042424936,0.00013163337],"domain_scores_gemma":[0.99850273,0.000045805704,0.00088514335,0.000268064,0.00021314033,0.00008509731],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012591413,0.000057597375,0.00012814626,0.00017932395,0.00016899577,0.00004886413,0.0013655166,0.000024405259,0.000007967513],"category_scores_gemma":[0.00046273333,0.00005767811,0.000010615016,0.00030266395,0.0001840133,0.0016740359,0.0002175601,0.000077760225,7.272596e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003157482,0.0003842957,0.7027799,0.00011958753,0.000019543284,0.0000011595481,0.0040405686,0.00009943876,0.006911888,0.0047496213,0.0010924793,0.2794858],"study_design_scores_gemma":[0.00035634005,0.00010349695,0.9742864,0.0000785798,0.00001699991,0.00009182099,0.0020822163,0.022123111,0.0003620936,0.00037823577,0.00005168526,0.00006903539],"about_ca_topic_score_codex":0.0005297086,"about_ca_topic_score_gemma":0.00006379608,"teacher_disagreement_score":0.27941674,"about_ca_system_score_codex":0.00007058652,"about_ca_system_score_gemma":0.0006616346,"threshold_uncertainty_score":0.25374922},"labels":[],"label_agreement":null},{"id":"W3111441188","doi":"10.23889/ijpds.v5i5.1441","title":"Using Machine Learning to Measure Specialist Wait Times from Family Physicians’ Electronic Medical Records Linked to Ontario Health Administrative Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Referral; Medical record; Electronic medical record; Medicine; Metric (unit); Family medicine; Electronic health record; Health care; Medical emergency; Business; Internal medicine","score_opus":0.3834122238163538,"score_gpt":0.5342300800192483,"score_spread":0.1508178562028945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111441188","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3433162,0.00045242076,0.15418787,0.4693919,0.016559077,0.0032417218,0.010609064,0.00021753742,0.0020242236],"genre_scores_gemma":[0.7384129,0.00016271243,0.047770564,0.190655,0.009869294,0.000025752212,0.011894359,0.00006609958,0.0011433198],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99532866,0.00028035266,0.0010137209,0.00076370646,0.0019454231,0.00066813966],"domain_scores_gemma":[0.9970634,0.000350071,0.0006058606,0.0005501241,0.0006331019,0.0007974636],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003217173,0.00018025823,0.00036096553,0.00020603884,0.0015932426,0.00016628073,0.0037847757,0.000085856256,0.0009778149],"category_scores_gemma":[0.003598831,0.00016722185,0.000045666857,0.00044704365,0.000051454932,0.001741085,0.0014357311,0.0012148736,0.000075162076],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031491371,0.00029247307,0.42120245,0.00009881135,0.00040922244,0.00006629422,0.024147984,0.00092961243,0.0018024719,0.009832968,0.33682224,0.20124635],"study_design_scores_gemma":[0.0011348067,0.00039530394,0.16007432,0.00036212505,0.000028563758,0.000011222621,0.0011125044,0.047060974,0.000003503494,0.00074865704,0.7887394,0.00032861895],"about_ca_topic_score_codex":0.06892366,"about_ca_topic_score_gemma":0.18844254,"teacher_disagreement_score":0.45191717,"about_ca_system_score_codex":0.0030050762,"about_ca_system_score_gemma":0.014702874,"threshold_uncertainty_score":0.99993545},"labels":[],"label_agreement":null},{"id":"W3111475963","doi":"10.23889/ijpds.v5i5.1438","title":"The Association of Sibling Fracture History with Major Osteoporotic Fractures in Individuals from A Population-Based Cohort","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Hip and Femur Fractures","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; University of Manitoba","funders":"","keywords":"Medicine; Sibling; Cohort; Proportional hazards model; Retrospective cohort study; Population; Hazard ratio; Cohort study; Medical record; Pediatrics; Demography; Internal medicine; Confidence interval; Environmental health; Psychology","score_opus":0.03117698847834497,"score_gpt":0.33773598743001987,"score_spread":0.3065589989516749,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111475963","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9785628,0.00024294195,0.0053722803,0.013984692,0.00087000453,0.0005425722,0.00032653668,0.000018819075,0.00007937267],"genre_scores_gemma":[0.99212027,0.000013403102,0.0035697496,0.002528455,0.00042508062,0.0000071245486,0.0012935481,0.000011881499,0.000030489295],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99739057,0.000043052452,0.00053594535,0.0003011317,0.0015448775,0.00018441658],"domain_scores_gemma":[0.99782383,0.00047492704,0.0007694456,0.0002608773,0.0005406694,0.00013023007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011811146,0.000115561925,0.00020590755,0.00025489824,0.00018306781,0.00012960422,0.0008024027,0.00007452406,0.000096262935],"category_scores_gemma":[0.003049509,0.00007613787,0.000051423067,0.00027880873,0.000063027466,0.00086299813,0.000062076826,0.00032127812,0.0000020119112],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021031976,0.000034580175,0.99328315,0.000005732148,0.000061029645,0.000003999312,0.00024592626,0.0031223542,0.00025966315,0.000063413056,0.0015357452,0.001174077],"study_design_scores_gemma":[0.0011781293,0.00007154207,0.97200054,0.00008810839,0.000065837405,0.0000061408823,0.00007250724,0.0142343175,0.00015384064,0.00028559292,0.011756984,0.00008645132],"about_ca_topic_score_codex":0.000847374,"about_ca_topic_score_gemma":0.00030324302,"teacher_disagreement_score":0.021282611,"about_ca_system_score_codex":0.00062923506,"about_ca_system_score_gemma":0.0004667824,"threshold_uncertainty_score":0.36507672},"labels":[],"label_agreement":null},{"id":"W3111514242","doi":"10.23889/ijpds.v5i5.1469","title":"Do Predictors of Children’s Special Educational Needs in Grade 3 Differ by Special Needs Status in Kindergarten in Ontario, Canada?","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Infant Development and Preterm Care","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University","funders":"","keywords":"Odds ratio; Confidence interval; Checklist; Demographics; Logistic regression; Psychology; Cohort; Developmental psychology; Medicine; Demography","score_opus":0.027802566864604614,"score_gpt":0.2952576435884355,"score_spread":0.26745507672383084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111514242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9924621,0.000016063226,0.000014877917,0.003510624,0.0024532168,0.00025984918,0.0006557246,0.0000024000685,0.00062513625],"genre_scores_gemma":[0.99403214,0.000013611836,0.00036937962,0.00038563096,0.0019457282,0.00000457881,0.0031771243,0.000007227854,0.00006459185],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977401,0.00002230732,0.0006376623,0.00023689198,0.0010975502,0.00026548072],"domain_scores_gemma":[0.9992518,0.00005525325,0.00020943387,0.00013564393,0.00017882853,0.00016906524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003872806,0.00011564814,0.00019596206,0.0007267063,0.00005195379,0.00007357544,0.0006608819,0.00004574207,0.00047032235],"category_scores_gemma":[0.00035822907,0.000111370835,0.000029363326,0.00059560355,0.00006670723,0.0008382231,0.00013120504,0.00031538427,5.1292386e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020553228,0.00003654921,0.9834461,0.0000035165472,0.000013719849,0.000006797986,0.002625443,0.000084341445,0.00015873261,0.00040743875,0.01246389,0.0005479459],"study_design_scores_gemma":[0.0016340002,0.00003965956,0.98603636,0.00008412596,0.000006458677,0.00003342216,0.00023031636,0.0005379999,0.00007426533,0.00019258034,0.011010442,0.000120392426],"about_ca_topic_score_codex":0.3072666,"about_ca_topic_score_gemma":0.7168188,"teacher_disagreement_score":0.40955222,"about_ca_system_score_codex":0.0011834215,"about_ca_system_score_gemma":0.002856256,"threshold_uncertainty_score":0.6973464},"labels":[],"label_agreement":null},{"id":"W3111548485","doi":"10.23889/ijpds.v5i5.1488","title":"Mental Disorders and Subsequent Suicide in A Representative Community Population","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Suicide and Self-Harm Studies","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Psychiatry; Hazard ratio; Population; Mental health; Anxiety; Medicine; Marital status; Suicide attempt; Major depressive episode; Cohort; Poison control; Psychology; Suicide prevention; Clinical psychology; Confidence interval; Medical emergency; Environmental health; Internal medicine; Mood","score_opus":0.17817894973148987,"score_gpt":0.46451735643888786,"score_spread":0.28633840670739796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111548485","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914209,0.00010445451,0.0010589763,0.0054923166,0.0011790053,0.00025243594,0.00019960228,0.00001745587,0.00027481283],"genre_scores_gemma":[0.9980662,0.00006824011,0.00071756024,0.000546696,0.00013037825,0.000009983605,0.0004277097,0.0000068983577,0.000026321399],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985957,0.00012862228,0.00036434655,0.00028532054,0.00044243844,0.00018352915],"domain_scores_gemma":[0.99922055,0.00015862775,0.00019669218,0.00020691572,0.000119158954,0.00009806838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009890781,0.00009278494,0.00011841602,0.00019487145,0.00041255448,0.00015410698,0.0008773928,0.000025681493,0.00006804349],"category_scores_gemma":[0.00066328706,0.000087019915,0.000027104752,0.0002518129,0.00013065504,0.0013545605,0.00037559035,0.0002347835,0.000005781628],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021847992,0.00006885404,0.9816303,0.0000026457728,0.00004118217,0.000005099864,0.0055095945,0.000092086535,0.00026947455,0.0032946304,0.0010161896,0.007851464],"study_design_scores_gemma":[0.00086858385,0.00006733941,0.9862446,0.000008035543,0.0000080086775,0.000028291019,0.0038612687,0.004817842,0.000014402527,0.003408144,0.0005707468,0.00010274318],"about_ca_topic_score_codex":0.0059355525,"about_ca_topic_score_gemma":0.0018682143,"teacher_disagreement_score":0.0077487207,"about_ca_system_score_codex":0.00010929197,"about_ca_system_score_gemma":0.000023382425,"threshold_uncertainty_score":0.89728194},"labels":[],"label_agreement":null},{"id":"W3111594579","doi":"10.23889/ijpds.v5i5.1471","title":"Evaluation of The Manitoba Healthy Baby Prenatal Benefit: Is It Improving Birth and Early Childhood Outcomes for Metis Families?","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Breastfeeding Practices and Influences","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Winnipeg; University of Manitoba","funders":"","keywords":"Metis; Medicine; Demography; Birth weight; Gestational age; Breastfeeding; Pediatrics; Low birth weight; Prenatal care; Relative risk; Pregnancy; Population; Environmental health; Confidence interval","score_opus":0.11600538274635819,"score_gpt":0.4042412168319461,"score_spread":0.2882358340855879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111594579","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9506211,0.00010629486,0.0012759841,0.046021447,0.0008543084,0.0005767316,0.000503751,0.0000068699123,0.00003349908],"genre_scores_gemma":[0.99407786,0.000039412367,0.004031075,0.0015144267,0.00027520655,0.000009004548,0.00003436249,0.0000064874994,0.0000121549765],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977862,0.000020486328,0.0003969251,0.00026629877,0.0013991683,0.00013092635],"domain_scores_gemma":[0.9978663,0.000110708446,0.0005156928,0.00018728478,0.0012134187,0.00010660167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002095139,0.00008096267,0.00013102934,0.0001147325,0.00028891474,0.00018224957,0.0006692545,0.000027646096,0.000020294488],"category_scores_gemma":[0.002975968,0.000054166772,0.00005678835,0.00017239335,0.00009194504,0.0020373778,0.00020693179,0.00011441337,6.1211944e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028757608,0.000087183726,0.55563974,0.000066903725,0.00015383006,3.6736708e-7,0.0016703409,0.00020685559,0.0009426348,0.0013588916,0.0005166419,0.43906906],"study_design_scores_gemma":[0.0013056545,0.00020801049,0.9522916,0.000087733264,0.0001256708,0.000058056376,0.00029417008,0.043777518,0.00023173027,0.0005157763,0.0010422542,0.00006183825],"about_ca_topic_score_codex":0.00042501028,"about_ca_topic_score_gemma":0.00006509803,"teacher_disagreement_score":0.43900722,"about_ca_system_score_codex":0.000079560676,"about_ca_system_score_gemma":0.0002888762,"threshold_uncertainty_score":0.35627264},"labels":[],"label_agreement":null},{"id":"W3111612896","doi":"10.23889/ijpds.v5i5.1525","title":"Shared Priorities, Data and Reporting: Improving Access to Mental Health, Addictions and Home Care Services","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Context (archaeology); Presentation (obstetrics); Comparability; Mental health; Government (linguistics); Business; Public relations; Political science; Medicine","score_opus":0.2798726208286516,"score_gpt":0.5483940761614229,"score_spread":0.2685214553327713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111612896","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49575105,0.0025599548,0.008560819,0.4406717,0.013747899,0.0035040802,0.03450629,0.00023723717,0.0004609391],"genre_scores_gemma":[0.9243295,0.00046067804,0.014108854,0.05142794,0.0018071765,0.000028108436,0.0077279704,0.000026221178,0.00008351983],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972955,0.000055982193,0.001123675,0.00057377655,0.00062925165,0.00032179867],"domain_scores_gemma":[0.9972869,0.00011353919,0.0011964508,0.00043797068,0.00048205844,0.00048308406],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0015904754,0.00010734436,0.00020972276,0.00019946611,0.002233297,0.0004373999,0.0020359072,0.00004182757,0.000044381537],"category_scores_gemma":[0.0011499465,0.00009783351,0.000015035112,0.00022533197,0.00004935036,0.0050476324,0.003254749,0.00028734864,0.0000031756945],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017459484,0.0000160399,0.8368912,0.00059579796,0.000033897777,0.00000756502,0.008601489,0.000010794702,0.00021665594,0.00073444634,0.055704903,0.09701263],"study_design_scores_gemma":[0.0010490638,0.00012206718,0.7095637,0.00028177112,0.00001791956,0.00007126375,0.0048358836,0.013117293,0.0000027705664,0.000267104,0.27044207,0.0002291573],"about_ca_topic_score_codex":0.0014357998,"about_ca_topic_score_gemma":0.0014730352,"teacher_disagreement_score":0.42857847,"about_ca_system_score_codex":0.00038608973,"about_ca_system_score_gemma":0.0014668271,"threshold_uncertainty_score":0.99906564},"labels":[],"label_agreement":null},{"id":"W3111616091","doi":"10.23889/ijpds.v5i5.1540","title":"Using Reproducible Data Visualizations to Augment Decision-Making During Suppression of Small Counts","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Workflow; Redaction; Computer science; Human error; Judgement; Data quality; Population; Data science; Medicine; Risk analysis (engineering); Database; Engineering; Operations management; Geography; Political science","score_opus":0.2227099826820303,"score_gpt":0.4798295732079889,"score_spread":0.2571195905259586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111616091","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52891463,0.00009222868,0.4685829,0.00060680177,0.0012282189,0.000092956245,0.00043199505,0.000007367705,0.000042900097],"genre_scores_gemma":[0.89916486,0.000019654846,0.1000222,0.00013900192,0.0003233458,5.454145e-7,0.00030934074,0.0000043776095,0.000016691009],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991104,0.000009296472,0.00020198454,0.00030684785,0.0002908511,0.00008060213],"domain_scores_gemma":[0.99924463,0.0000141126675,0.00011451286,0.00037488856,0.00019219183,0.00005969152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042019278,0.00004098582,0.00005075942,0.000062338084,0.000114785165,0.00005714191,0.0012328369,0.000024218527,0.00001935411],"category_scores_gemma":[0.002759053,0.00003566782,0.000012720551,0.00012335846,0.00004232442,0.000034289453,0.0008249559,0.00003245354,0.0000017057407],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049919455,0.00012766731,0.024187885,0.000036864734,0.000089925255,0.000007930406,0.00023648777,0.013635742,0.75757074,0.00042147387,0.019946972,0.18323913],"study_design_scores_gemma":[0.0018314909,0.000458618,0.082682304,0.0010003529,0.00008131191,0.00027227864,0.00039090996,0.57608056,0.06749326,0.0012858033,0.2676691,0.0007539856],"about_ca_topic_score_codex":0.000007798876,"about_ca_topic_score_gemma":0.0000039141996,"teacher_disagreement_score":0.6900775,"about_ca_system_score_codex":0.000015724128,"about_ca_system_score_gemma":0.00008562053,"threshold_uncertainty_score":0.33030435},"labels":[],"label_agreement":null},{"id":"W3111675758","doi":"10.23889/ijpds.v5i5.1557","title":"Building Research Capacity and Organizational Empathy Among Students: Making Connections Beyond the Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"General partnership; Public relations; Empathy; Government (linguistics); Inclusion (mineral); Qualitative property; Population; Sociology; Knowledge management; Political science; Psychology; Social psychology; Computer science","score_opus":0.5841194732396603,"score_gpt":0.5729072787363005,"score_spread":0.011212194503359751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111675758","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6485678,0.00015032098,0.33539516,0.010297443,0.0038509835,0.0004732467,0.0009978197,0.000033121756,0.0002341046],"genre_scores_gemma":[0.98706156,0.0000058873466,0.01114241,0.00057131273,0.0010996026,0.000003420603,0.00005159142,0.000010716731,0.000053494954],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9906572,0.0002751191,0.0009737284,0.0009841411,0.006774982,0.0003347898],"domain_scores_gemma":[0.99175346,0.0027045223,0.0005841891,0.0012984986,0.003423402,0.00023595567],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.021094559,0.00012173532,0.00018019987,0.0005681753,0.0028507893,0.006245295,0.012559336,0.000039911167,0.00015737026],"category_scores_gemma":[0.04205664,0.00008105966,0.000035935427,0.0019538135,0.00050628476,0.005489781,0.006737594,0.00038590436,0.00002134222],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000111887915,0.00009344625,0.58919466,0.000005259149,0.00008586458,0.000018736459,0.0026196134,0.002901095,0.0012425723,0.3114211,0.06876871,0.023537043],"study_design_scores_gemma":[0.00055777794,0.000051545067,0.3535432,0.000060772338,0.000013798115,0.0002423212,0.0027146342,0.44426554,0.000015620586,0.15485783,0.04346454,0.00021241486],"about_ca_topic_score_codex":0.000112877606,"about_ca_topic_score_gemma":0.00018502981,"teacher_disagreement_score":0.44136447,"about_ca_system_score_codex":0.00011314135,"about_ca_system_score_gemma":0.00021503029,"threshold_uncertainty_score":0.99844736},"labels":[],"label_agreement":null},{"id":"W3111697991","doi":"10.23889/ijpds.v5i5.1478","title":"Using Linked Data to Examine the Epidemiology of All-Cause and Cause-Specific Mortality Following Release from Incarceration in Eleven Countries","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Criminal Justice and Corrections Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Medicine; Epidemiology; Public health; Demography; Incidence (geometry); Mortality rate; Environmental health; Gerontology; Surgery; Pathology","score_opus":0.5349374582819344,"score_gpt":0.5122787362734462,"score_spread":0.022658722008488175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111697991","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9626096,0.00014192043,0.031696178,0.0044387477,0.0005882833,0.00015637114,0.00035461393,0.000006715501,0.00000758362],"genre_scores_gemma":[0.99487436,0.00030493952,0.0034505888,0.00053482753,0.00049223425,0.0000020337316,0.00033290972,0.000003930464,0.000004152341],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99817294,0.00018531828,0.00051813095,0.00036815312,0.00059062924,0.00016483263],"domain_scores_gemma":[0.9983629,0.0005959424,0.00028787367,0.00036097172,0.00026934687,0.00012299213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034497448,0.00006936709,0.0001562073,0.00015875394,0.0004772721,0.0001656537,0.0015414988,0.00003455998,0.000022357774],"category_scores_gemma":[0.0052064313,0.000057911464,0.00002912009,0.00044194495,0.00017949117,0.0019168936,0.00043460354,0.00012192571,0.0000012653024],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024553316,0.000077448465,0.9364963,0.000009299947,0.00033211394,0.000022568547,0.015569986,0.012568884,0.0035065056,0.0087931,0.0008660436,0.021512175],"study_design_scores_gemma":[0.00050202344,0.00005392519,0.4459333,0.000098066776,0.0004353731,0.000009229368,0.02832443,0.51366496,0.000026795313,0.0016194338,0.009094507,0.00023793116],"about_ca_topic_score_codex":0.019063786,"about_ca_topic_score_gemma":0.02309674,"teacher_disagreement_score":0.50109607,"about_ca_system_score_codex":0.00013120005,"about_ca_system_score_gemma":0.0002195088,"threshold_uncertainty_score":0.9947292},"labels":[],"label_agreement":null},{"id":"W3111728018","doi":"10.23889/ijpds.v5i5.1421","title":"Trends in diabetes medications in Canada, England, Scotland and Australia: a repeated cross-sectional analysis (2012-2017)","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Diabetes Treatment and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Metformin; Medicine; Sulfonylurea; Diabetes mellitus; Medical prescription; Type 2 diabetes; Drug class; Internal medicine; Endocrinology; Pharmacology; Drug","score_opus":0.08260748629867751,"score_gpt":0.38886614170050915,"score_spread":0.3062586554018316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111728018","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954748,0.00004832844,0.00017620799,0.0035260166,0.00033259156,0.00011588358,0.00024710307,0.000006353823,0.00007267334],"genre_scores_gemma":[0.99699813,0.000021707387,0.00065158954,0.00025494717,0.00013560412,0.000008681958,0.0016902322,0.000003752997,0.00023535082],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983734,0.000015689913,0.0004095347,0.0003394325,0.00065306027,0.00020891467],"domain_scores_gemma":[0.99926805,0.0000502018,0.00015470272,0.0001653771,0.00016762712,0.00019406174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006456983,0.00008390279,0.0001623557,0.00079915894,0.00009079087,0.00015555929,0.0003939477,0.0000233671,0.0001470417],"category_scores_gemma":[0.00030506632,0.00007263378,0.00003363972,0.00095580454,0.000064844346,0.0009310377,0.0001211254,0.000114165414,0.0000013663605],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004229003,0.000031361746,0.9953421,0.0000038104054,0.00014927701,0.000015874382,0.00003802378,0.0006126126,0.000060010618,0.00011113993,0.00037400404,0.0032195402],"study_design_scores_gemma":[0.0014107132,0.000033619166,0.96032596,0.00001673169,0.00008736073,0.000007500457,0.00001700131,0.0358596,0.000011491869,0.00004816041,0.0021171689,0.00006471377],"about_ca_topic_score_codex":0.06994687,"about_ca_topic_score_gemma":0.4100449,"teacher_disagreement_score":0.34009805,"about_ca_system_score_codex":0.00042292764,"about_ca_system_score_gemma":0.0002514228,"threshold_uncertainty_score":0.93624645},"labels":[],"label_agreement":null},{"id":"W3111762657","doi":"10.23889/ijpds.v5i5.1621","title":"MASK: A Success Story for An International Collaboration","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Identification (biology); Masking (illustration); Process (computing); Protected health information; Software; Interface (matter); Artificial intelligence; Machine learning; Information retrieval; Data science; World Wide Web; Public health","score_opus":0.09876678348695475,"score_gpt":0.4311233464971597,"score_spread":0.332356563010205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111762657","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5554762,0.00013314644,0.41424158,0.019553274,0.007939059,0.00045419973,0.0019811587,0.000045158948,0.00017624626],"genre_scores_gemma":[0.95309633,0.000047914375,0.04044664,0.0011563352,0.0021558406,0.000015224689,0.002972085,0.00001034228,0.000099279794],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987598,0.00002405084,0.00023085286,0.00038669977,0.00045117745,0.00014743944],"domain_scores_gemma":[0.998763,0.00002688884,0.00018640811,0.0002109722,0.00066280697,0.00014989472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074716425,0.000081406906,0.000073535295,0.00008455963,0.0002495675,0.00030389536,0.0018371969,0.00006137895,0.000012951097],"category_scores_gemma":[0.0021562297,0.00007487535,0.000036228223,0.00011289478,0.00012783015,0.00017897534,0.00022060363,0.00007431904,0.0000018439198],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029479412,0.00036923902,0.04892955,0.000039631595,0.00034334866,0.0000087632125,0.0010599429,0.0026164467,0.40364957,0.008204036,0.099388495,0.43244302],"study_design_scores_gemma":[0.0018986601,0.0008073001,0.018384697,0.000023402135,0.000022632146,0.000056951383,0.00051473273,0.08505263,0.0060047125,0.0006857642,0.8862293,0.0003192444],"about_ca_topic_score_codex":0.0000086638,"about_ca_topic_score_gemma":0.0000341574,"teacher_disagreement_score":0.7868408,"about_ca_system_score_codex":0.000041034484,"about_ca_system_score_gemma":0.00021470545,"threshold_uncertainty_score":0.34139994},"labels":[],"label_agreement":null},{"id":"W3111922890","doi":"10.23889/ijpds.v5i5.1437","title":"Using Additive and Relative Hazards to Quantify Colorectal Survival Inequalities for Patients with A Severe Psychiatric Illness","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Queen's University; Sunnybrook Health Science Centre; Centre for Addiction and Mental Health; University of Manitoba","funders":"","keywords":"Medicine; Proportional hazards model; Hazard ratio; Cohort; Colorectal cancer; Bipolar disorder; Schizophrenia (object-oriented programming); Mental illness; Relative risk; Retrospective cohort study; Depression (economics); Psychiatric history; Psychiatry; Internal medicine; Cancer; Mental health; Mood; Confidence interval","score_opus":0.12232343385283925,"score_gpt":0.44138104292595676,"score_spread":0.31905760907311753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111922890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9641352,0.000015096297,0.01998902,0.009915039,0.0022162492,0.0007174746,0.0028410256,0.000019037501,0.00015182879],"genre_scores_gemma":[0.98261064,0.000015304267,0.015553394,0.0010015835,0.00060467026,0.00001115448,0.00016902198,0.000008548306,0.00002566886],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980964,0.00006698875,0.00030161417,0.00030570358,0.00094233116,0.00028697067],"domain_scores_gemma":[0.9980003,0.00036877685,0.00023426802,0.000077242854,0.0010173422,0.00030204307],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0009941747,0.00009079687,0.00014289541,0.00014725229,0.0013387594,0.00041783095,0.0006848444,0.000036715668,0.000028035422],"category_scores_gemma":[0.0032583699,0.00007693174,0.000027775575,0.0003559844,0.00016607261,0.0024784412,0.00014449633,0.00009303302,9.455683e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011523109,0.00009645877,0.7914011,0.000045214274,0.0000793887,0.00000169592,0.0148735475,0.00033565922,0.00000622698,0.17598553,0.0014866701,0.014536184],"study_design_scores_gemma":[0.002572883,0.000514494,0.9194227,0.00016868525,0.00005914171,0.0000067315705,0.012533409,0.024746822,0.0000070859287,0.0044259285,0.034990273,0.0005518687],"about_ca_topic_score_codex":0.0010251679,"about_ca_topic_score_gemma":0.00088383333,"teacher_disagreement_score":0.1715596,"about_ca_system_score_codex":0.00019079715,"about_ca_system_score_gemma":0.00058198156,"threshold_uncertainty_score":0.9999614},"labels":[],"label_agreement":null},{"id":"W3111951434","doi":"10.23889/ijpds.v5i5.1530","title":"Opioid Agonist Treatment and Risk of Mortality During an Opioid Overdose Public Health Emergency: A Population-Based Retrospective Cohort Study","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University; Ministry of Health; BC Children's Hospital; BC Centre for Disease Control; AIDS Vancouver","funders":"","keywords":"Medicine; Fentanyl; Cohort; Population; Drug overdose; Opioid use disorder; Emergency medicine; Retrospective cohort study; Cohort study; Public health; Opioid; Anesthesia; Internal medicine; Poison control; Environmental health","score_opus":0.082721987471555,"score_gpt":0.4074192937123322,"score_spread":0.3246973062407772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111951434","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943932,0.0000813296,0.0009585139,0.0012621302,0.00059887086,0.0012805925,0.0013836096,0.000032162934,0.000009547032],"genre_scores_gemma":[0.9957569,0.0002816831,0.0018120955,0.00007288674,0.00021894765,0.00002990813,0.0017998152,0.000016742262,0.0000109810135],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99713653,0.0000894983,0.00074105046,0.0006534607,0.0011278286,0.00025165096],"domain_scores_gemma":[0.9977011,0.000026891968,0.000724815,0.00051044277,0.0005996514,0.0004370675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097642164,0.00018548672,0.00035629567,0.000260359,0.00050887896,0.00015358395,0.0005023846,0.000029411836,0.00005855934],"category_scores_gemma":[0.0007475,0.00015724996,0.00007380882,0.00037351288,0.000071885115,0.0012922958,0.00013451,0.00012207424,0.0000010642369],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014968433,0.000895208,0.99595547,0.000019911127,0.000253261,0.000004877336,0.000954563,0.00018347052,0.00009411089,0.00012970278,0.000016971315,0.0013427773],"study_design_scores_gemma":[0.0023549553,0.0011676057,0.9775151,0.000023990297,0.00013668709,0.000013537964,0.00034585968,0.018064383,0.000039573373,0.00017325055,0.000049869595,0.00011516693],"about_ca_topic_score_codex":0.005778262,"about_ca_topic_score_gemma":0.00067023933,"teacher_disagreement_score":0.018440343,"about_ca_system_score_codex":0.0009135493,"about_ca_system_score_gemma":0.00064998626,"threshold_uncertainty_score":0.8735042},"labels":[],"label_agreement":null},{"id":"W3111976332","doi":"10.23889/ijpds.v5i5.1523","title":"Peripheral Arterial Disease Among First Nations People with Diabetes in Ontario, Canada: Linkage of Population-Level Healthcare Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Diabetic Foot Ulcer Assessment and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; Laurentian University; University of Toronto","funders":"","keywords":"Medicine; Amputation; Hazard ratio; Diabetes mellitus; Population; Arterial disease; Revascularization; Demography; Gerontology; Type 2 diabetes; Health care; Disease; Confidence interval; Environmental health; Vascular disease; Internal medicine; Surgery; Myocardial infarction; Economic growth","score_opus":0.06782102328694457,"score_gpt":0.33331340137035986,"score_spread":0.2654923780834153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111976332","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98068714,0.000015254823,0.0013305667,0.015040028,0.0010450992,0.0005479144,0.0012421043,0.00001092726,0.00008098117],"genre_scores_gemma":[0.98883104,0.000005647316,0.0032402738,0.00038343834,0.00022300614,0.000011967825,0.0072294576,0.0000100035095,0.00006515051],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977795,0.00001615641,0.00047535053,0.00040169636,0.00111668,0.00021060032],"domain_scores_gemma":[0.99858475,0.000062011546,0.00027819315,0.0004494958,0.0003547176,0.00027084115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004031104,0.000111093155,0.00019010012,0.00021904627,0.00021312002,0.0001416733,0.0011564816,0.000019155392,0.0001115821],"category_scores_gemma":[0.0005957169,0.00009713388,0.000022279877,0.00034989588,0.00006186333,0.0016533256,0.00038284692,0.00014218065,3.525638e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001313127,0.00006720422,0.99605066,0.00004945748,0.000039673763,0.0000084561125,0.00012233897,0.000951364,0.000012357706,0.0009068516,0.0011719547,0.0004883532],"study_design_scores_gemma":[0.0010546081,0.000068779205,0.93507314,0.0001763783,0.00004315726,0.0000018510927,0.000088511515,0.061155245,0.0000026413,0.00006839798,0.0021711257,0.0000961909],"about_ca_topic_score_codex":0.56974757,"about_ca_topic_score_gemma":0.98555243,"teacher_disagreement_score":0.4158049,"about_ca_system_score_codex":0.0005399802,"about_ca_system_score_gemma":0.0014384228,"threshold_uncertainty_score":0.43311754},"labels":[],"label_agreement":null},{"id":"W3112060305","doi":"10.23889/ijpds.v5i5.1499","title":"Canadian Data Platform: Developing an Algorithm Inventory for Health and Social Measures","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information; University of Manitoba","funders":"","keywords":"Standardization; Computer science; MEDLINE; Algorithm; Population; Population health; Resource (disambiguation); Data extraction; Data science; Data mining; Medicine; Environmental health; Political science","score_opus":0.4618540837166018,"score_gpt":0.5535471866697054,"score_spread":0.09169310295310357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112060305","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024463931,0.0005632029,0.31251642,0.62623096,0.013126636,0.0027349258,0.01996718,0.00013475932,0.00026200069],"genre_scores_gemma":[0.22410142,0.0005942418,0.27805278,0.44687966,0.012148882,0.000088892404,0.037780304,0.000089684945,0.00026414669],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978149,0.00006771695,0.0006033895,0.00043095427,0.0006036871,0.00047937236],"domain_scores_gemma":[0.9981041,0.000115360475,0.000379951,0.0002785241,0.00048181272,0.0006402283],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0029371574,0.000099236895,0.00017692597,0.00023653825,0.0029382696,0.0001484259,0.0021709143,0.00006203219,0.000021476539],"category_scores_gemma":[0.0008825537,0.000092816335,0.000018742772,0.00014723641,0.000060669558,0.0036058715,0.00052490586,0.00027022374,0.000003583253],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021981235,0.00002396171,0.0670606,0.00021884954,0.00007227791,0.000005147181,0.007276898,0.000009588033,0.000029005161,0.021933835,0.32214582,0.5810042],"study_design_scores_gemma":[0.0010692548,0.00009731494,0.022777019,0.000053528573,0.000010224932,0.000015222136,0.0015074804,0.051201556,9.798082e-7,0.002923166,0.92013913,0.00020509008],"about_ca_topic_score_codex":0.017920313,"about_ca_topic_score_gemma":0.06139645,"teacher_disagreement_score":0.5979934,"about_ca_system_score_codex":0.0012284849,"about_ca_system_score_gemma":0.01127232,"threshold_uncertainty_score":0.99835974},"labels":[],"label_agreement":null},{"id":"W3112077244","doi":"10.23889/ijpds.v5i5.1466","title":"Prevalence of Blood-Borne Viral Infections (HIV, HBV, HCV) Among People Seeking Fertility Services in Ontario, Canada","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"HIV, Drug Use, Sexual Risk","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"Medicine; Population; Incidence (geometry); Viral hepatitis; Hepatitis C; Cumulative incidence; Family medicine; Interquartile range; Public health; Demography; Viral load; Environmental health; Cohort; Immunology; Internal medicine; Human immunodeficiency virus (HIV); Nursing","score_opus":0.05222707532554166,"score_gpt":0.3513602107850655,"score_spread":0.29913313545952386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112077244","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99579805,0.000022467317,0.0011438995,0.0015186947,0.0007115253,0.00026167795,0.00035382767,0.000014627302,0.0001752585],"genre_scores_gemma":[0.99789864,0.000010819271,0.0012955953,0.00025378793,0.00014226974,0.0000051867746,0.00026552586,0.0000090506,0.00011913789],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974657,0.000032896103,0.00065198034,0.00040547128,0.0011875811,0.00025633647],"domain_scores_gemma":[0.99837786,0.00008989353,0.00037919742,0.00032561916,0.0005748068,0.00025265256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007804771,0.000121908546,0.0002020064,0.00021574221,0.00017650572,0.00010238096,0.001127845,0.000037708698,0.00017043785],"category_scores_gemma":[0.00092959584,0.000116000345,0.000039625393,0.00041917845,0.00009042469,0.0019109971,0.0003138624,0.00033118064,0.0000019829931],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008903664,0.00008931997,0.9948928,0.000065772474,0.00002664601,0.000010933567,0.0012234852,0.0012451926,0.0012382235,0.00006235368,0.00012447592,0.000931767],"study_design_scores_gemma":[0.000696134,0.00008172748,0.95284885,0.0001728939,0.000056428937,0.000040065835,0.00042380465,0.04475775,0.00029756743,0.0000993897,0.00042965976,0.000095701056],"about_ca_topic_score_codex":0.7621315,"about_ca_topic_score_gemma":0.95705914,"teacher_disagreement_score":0.19492763,"about_ca_system_score_codex":0.0004718415,"about_ca_system_score_gemma":0.0015088619,"threshold_uncertainty_score":0.4730357},"labels":[],"label_agreement":null},{"id":"W3112120821","doi":"10.23889/ijpds.v5i5.1628","title":"A Comparison of The Health Impacts of Individual Level and Area Based Welsh Government Fuel Poverty Schemes","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Energy and Environment Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"","keywords":"Welsh; Fuel poverty; Poverty; Psychological intervention; Environmental health; Government (linguistics); Residence; Intervention (counseling); Medicine; Geography; Demography; Economic growth; Economics; Protocol (science); Sociology; Nursing","score_opus":0.1462473863273177,"score_gpt":0.37099046301236177,"score_spread":0.22474307668504406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112120821","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9852589,0.00004868284,0.007016395,0.006345484,0.00029618372,0.00013792288,0.00080544926,0.00000383728,0.000087143475],"genre_scores_gemma":[0.9948203,0.000015432333,0.0038008501,0.001279472,0.000028906099,7.9161015e-7,0.000042350584,0.000003736247,0.000008135676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977999,0.000026976335,0.00035442077,0.00019232932,0.0014827849,0.00014361081],"domain_scores_gemma":[0.9990793,0.0000500087,0.0005072052,0.00019209586,0.0000173312,0.0001540826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072354317,0.00007484597,0.00011675021,0.000022601069,0.00015565394,0.00005892084,0.0012298126,0.00001967209,0.00010658684],"category_scores_gemma":[0.00047781962,0.000052290332,0.000031577114,0.00015426871,0.00023121336,0.0009281475,0.0006155242,0.000088336245,9.682885e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008549252,0.000109899884,0.9628152,0.000011959815,0.000019404308,2.5224216e-7,0.0004057229,0.016620612,0.0065820883,0.00027095352,0.0025455453,0.0105328215],"study_design_scores_gemma":[0.0004146903,0.0001307362,0.9641542,0.000035521996,0.000008381768,0.0000051721872,0.000088492714,0.029606452,0.003230389,0.00015332134,0.0021092864,0.00006334989],"about_ca_topic_score_codex":0.00015909738,"about_ca_topic_score_gemma":0.00009099633,"teacher_disagreement_score":0.01298584,"about_ca_system_score_codex":0.0001479657,"about_ca_system_score_gemma":0.00005461669,"threshold_uncertainty_score":0.22853184},"labels":[],"label_agreement":null},{"id":"W3112138720","doi":"10.23889/ijpds.v5i5.1453","title":"Identifying Prenatal Opioid Exposure in Health Administrative Data for Public Health Surveillance and Epidemiologic Research","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Prenatal Substance Exposure Effects","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"St. Michael's Hospital; SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Medicine; Public health; Medical prescription; Population; Pregnancy; Addiction; Environmental health; Prenatal care; Psychiatry; Medical emergency; Nursing","score_opus":0.5619136415318949,"score_gpt":0.5494367765810309,"score_spread":0.012476864950864086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112138720","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5229357,0.008236746,0.18325949,0.26669094,0.00372705,0.00539249,0.0095990095,0.000114258546,0.000044305834],"genre_scores_gemma":[0.9692067,0.00035323657,0.024855258,0.0012791204,0.0005365671,0.000022491655,0.0037209995,0.000012156618,0.000013509107],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99625224,0.00033911588,0.00084732944,0.0008589885,0.0011350509,0.0005672621],"domain_scores_gemma":[0.9967127,0.0010075353,0.000504121,0.0006071262,0.0006249186,0.00054362917],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.018347194,0.0001280572,0.0003369345,0.00034617167,0.00045099444,0.0003322462,0.0020745057,0.000046284073,0.000008630245],"category_scores_gemma":[0.023429465,0.00011121113,0.00002847954,0.00058280333,0.0002416599,0.0028806943,0.0008806236,0.00043611272,0.000001716044],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016370929,0.0003426341,0.79118085,0.0009885042,0.00013980397,0.00006619952,0.0028093096,0.000112312984,0.001599519,0.014915955,0.018914396,0.16729344],"study_design_scores_gemma":[0.003980178,0.0019071645,0.8571412,0.0007778614,0.0000043185937,0.0004076306,0.0008379348,0.11125143,0.00008412393,0.0035737758,0.019747872,0.0002865385],"about_ca_topic_score_codex":0.00017802787,"about_ca_topic_score_gemma":0.0004501412,"teacher_disagreement_score":0.44627094,"about_ca_system_score_codex":0.00041712675,"about_ca_system_score_gemma":0.0014937229,"threshold_uncertainty_score":0.9847966},"labels":[],"label_agreement":null},{"id":"W3112205323","doi":"10.23889/ijpds.v5i5.1467","title":"Use of Machine Learning and Linked Population Health Data to Develop Predictive Risk Algorithms for Population Health Decision-Making","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"Computer science; Machine learning; Population health; Population; Overfitting; Artificial intelligence; Health care; Data mining; Data science; Artificial neural network; Medicine; Environmental health","score_opus":0.20740493143922126,"score_gpt":0.4937614469410697,"score_spread":0.2863565155018485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112205323","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.105188824,0.00034234903,0.8466875,0.037067734,0.002526088,0.0018878827,0.0062191216,0.00007556821,0.000004951253],"genre_scores_gemma":[0.73197824,0.0005588157,0.26101258,0.003117627,0.0006518166,0.000007967142,0.0026413694,0.000016090713,0.000015466601],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99641335,0.00022268208,0.0010336583,0.0005983312,0.0012947149,0.00043724183],"domain_scores_gemma":[0.9961511,0.0010080297,0.0011728575,0.00026967042,0.00090196275,0.0004963777],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.00595105,0.00013368952,0.00029789418,0.0003105003,0.0020338784,0.000507503,0.0013479765,0.00005713357,0.000013630341],"category_scores_gemma":[0.02030519,0.00012973804,0.000033703425,0.0006957881,0.00008219128,0.003840014,0.0005113607,0.00022170033,8.095302e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001840561,0.000027172782,0.50999886,0.000039442974,0.000024010369,3.9815268e-7,0.0022269955,0.003489046,0.0000016392077,0.0027598026,0.0015610424,0.47968757],"study_design_scores_gemma":[0.00033436922,0.00013130593,0.5917043,0.00022991728,0.000009483175,0.0000035663907,0.0005026838,0.37492296,2.7402749e-7,0.0012409368,0.030795997,0.00012416266],"about_ca_topic_score_codex":0.022525704,"about_ca_topic_score_gemma":0.007330469,"teacher_disagreement_score":0.62678945,"about_ca_system_score_codex":0.00043719524,"about_ca_system_score_gemma":0.000867027,"threshold_uncertainty_score":0.9992653},"labels":[],"label_agreement":null},{"id":"W3112222062","doi":"10.23889/ijpds.v5i5.1626","title":"Planting the S.E.E.D.S of Indigenous Population Health Data Linkage","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Indigenous; Sovereignty; Linkage (software); Linked data; Population; Data governance; Sociology; Political science; Public relations; Law; Business; World Wide Web; Service (business); Data quality; Computer science; Ecology; Politics; Genetics","score_opus":0.12298225536536102,"score_gpt":0.3983579672825561,"score_spread":0.2753757119171951,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112222062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91988635,0.000077894285,0.06018775,0.016302887,0.0011478617,0.0008608797,0.0013142613,0.00003517747,0.00018690995],"genre_scores_gemma":[0.98816335,0.00008486137,0.0074673933,0.0026683027,0.00032791146,0.000002558027,0.0012613342,0.000012055519,0.000012232246],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99694437,0.00010061625,0.000660799,0.00061673956,0.001359112,0.0003183739],"domain_scores_gemma":[0.998073,0.00016282151,0.0007890186,0.00073028967,0.000045272467,0.00019962326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040666475,0.000110506466,0.00014034758,0.00007942162,0.0007488682,0.00017578558,0.0041039544,0.000029780314,0.00013477636],"category_scores_gemma":[0.0014656889,0.00008759272,0.000027810389,0.00034927946,0.00019668859,0.002993342,0.0015713944,0.00024456726,0.000032077023],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000071273564,0.00009829201,0.75559974,0.00002421081,0.000034996443,0.000006647903,0.0024756396,0.009752589,0.0023018597,0.00043396212,0.0028965173,0.22630428],"study_design_scores_gemma":[0.00037179186,0.00007303988,0.8503641,0.000050690483,0.000011751007,0.00005299752,0.0002466177,0.13445267,0.000099389414,0.0005038933,0.013623258,0.00014980414],"about_ca_topic_score_codex":0.0017975917,"about_ca_topic_score_gemma":0.00023996425,"teacher_disagreement_score":0.22615448,"about_ca_system_score_codex":0.00024982865,"about_ca_system_score_gemma":0.000107544634,"threshold_uncertainty_score":0.7626237},"labels":[],"label_agreement":null},{"id":"W3112282974","doi":"10.23889/ijpds.v5i5.1473","title":"Ethical Data Linkage with Indigenous Communities: The Manitoba Experience","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"First Nations Health and Social Secretariat of Manitoba; University of Manitoba","funders":"","keywords":"Indigenous; General partnership; Colonialism; Data sharing; Population health; Health equity; Population; Metis; Political science; Economic growth; Public relations; Sociology; Medicine; Environmental health; Law; Health care","score_opus":0.1704037461536932,"score_gpt":0.4428095480835894,"score_spread":0.2724058019298962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112282974","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92009175,0.00018297146,0.030124547,0.03499012,0.006973969,0.0015195155,0.0010408307,0.00012174781,0.004954559],"genre_scores_gemma":[0.9887143,0.0013822267,0.0045110034,0.001986968,0.0024894183,0.0000034083646,0.0007577465,0.000011941606,0.00014298133],"study_design_codex":"qualitative","study_design_gemma":"not_applicable","domain_scores_codex":[0.99695486,0.00022983742,0.0003837908,0.00033714029,0.001692394,0.00040200053],"domain_scores_gemma":[0.9973725,0.0003649086,0.00032910903,0.0008111583,0.0008462398,0.00027607428],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0037581164,0.000106839834,0.00010878464,0.000108871274,0.01260222,0.0010332821,0.0088914875,0.00008793549,0.00006852071],"category_scores_gemma":[0.00022618946,0.00006833597,0.000021874519,0.00044573398,0.0010141094,0.003063156,0.00008872781,0.0005891085,0.000016743581],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011109038,0.000108306966,0.016993513,0.000012247614,0.000041315976,0.00001035537,0.8764938,0.00017141264,0.000007329109,0.099677175,0.0012845638,0.00508889],"study_design_scores_gemma":[0.00025244,0.0000733862,0.0050626565,0.000043226402,0.0000142862755,0.000048991835,0.05216073,0.0033844737,0.000008174397,0.00079911127,0.93798316,0.00016934185],"about_ca_topic_score_codex":0.079525515,"about_ca_topic_score_gemma":0.4731267,"teacher_disagreement_score":0.9366986,"about_ca_system_score_codex":0.00023075477,"about_ca_system_score_gemma":0.0077759554,"threshold_uncertainty_score":0.99784905},"labels":[],"label_agreement":null},{"id":"W3112337930","doi":"10.23889/ijpds.v5i5.1562","title":"Healthcare Use for Violent Injury After Intimate Partner Violence Identified Through the Justice System: A Data Linkage Study","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Intimate Partner and Family Violence","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Saint Paul University; University of Manitoba; Manitoba Health","funders":"","keywords":"Domestic violence; Medicine; Hazard ratio; Population; Health care; Emergency department; Occupational safety and health; Poison control; Confidence interval; Demography; Medical record; Injury prevention; Medical emergency; Psychiatry; Environmental health; Political science; Surgery; Internal medicine","score_opus":0.22223502348018193,"score_gpt":0.4827458270826259,"score_spread":0.260510803602444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112337930","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4603882,0.00079984916,0.44917682,0.017520335,0.04198052,0.010868511,0.01787504,0.00040759286,0.0009831202],"genre_scores_gemma":[0.99304354,0.00013833267,0.0030665335,0.0015788387,0.0016142786,0.00010758821,0.00039337724,0.000017818073,0.000039682123],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959514,0.00020306477,0.0007695769,0.0008669379,0.0016863628,0.00052261463],"domain_scores_gemma":[0.996551,0.00040448247,0.00049676327,0.0010189452,0.0012852228,0.0002435853],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0038730472,0.00018577666,0.00020627622,0.00010676429,0.002143363,0.0019486098,0.006501181,0.00006159437,0.000033057266],"category_scores_gemma":[0.0027477723,0.00014141724,0.000068332505,0.0004917979,0.00038523827,0.0068734107,0.0013390708,0.0002631767,0.000032572047],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0053759413,0.0014434614,0.15958269,0.0008700789,0.0007582818,0.00015195081,0.0620789,0.0025585743,0.0005995898,0.6341054,0.043190163,0.089285016],"study_design_scores_gemma":[0.0030838274,0.00089350203,0.3947429,0.0019986953,0.001415311,0.00007361756,0.07785774,0.4129394,0.00007155041,0.006858479,0.09824994,0.0018150123],"about_ca_topic_score_codex":0.00278223,"about_ca_topic_score_gemma":0.00043028625,"teacher_disagreement_score":0.62724686,"about_ca_system_score_codex":0.00023665362,"about_ca_system_score_gemma":0.00041593867,"threshold_uncertainty_score":0.9991557},"labels":[],"label_agreement":null},{"id":"W3112344885","doi":"10.23889/ijpds.v5i5.1448","title":"Statistic Canada’s Longitudinal Social Data Development Program (LSDDP)","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Agency (philosophy); Identification (biology); Presentation (obstetrics); Data science; Reciprocity (cultural anthropology); Statistic; Life course approach; Modernization theory; Sociology; Computer science; Political science; Psychology; Social science; Social psychology; Statistics","score_opus":0.5750903712261164,"score_gpt":0.5311350515991244,"score_spread":0.04395531962699195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112344885","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18807746,0.00007508802,0.76829094,0.030307632,0.00755434,0.00069159357,0.0044210847,0.00011098872,0.0004708913],"genre_scores_gemma":[0.9467845,0.0000064847554,0.05010384,0.00056707166,0.000546559,0.0000055266196,0.0019157715,0.0000085819365,0.00006166561],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99338734,0.000053781394,0.00097464444,0.0008557006,0.0044259536,0.00030255932],"domain_scores_gemma":[0.9967231,0.00027127817,0.0006035174,0.0005944516,0.0015436925,0.000263961],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0042605684,0.0001287512,0.00016990109,0.00023714844,0.0009700669,0.0015820261,0.0073619736,0.000029564302,0.0001053278],"category_scores_gemma":[0.0065239263,0.00010563089,0.000029693103,0.0006887663,0.00012468164,0.0032360686,0.0010844831,0.00016583943,0.000018087836],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014428735,0.00010866385,0.036641564,0.000006248751,0.00006707461,0.00002708681,0.00049808354,0.002456044,0.00008350302,0.00447581,0.104805596,0.850686],"study_design_scores_gemma":[0.0004537039,0.00004052521,0.17637454,0.000013950363,0.000017471073,0.000040890918,0.00039727567,0.6308737,0.0000088812885,0.0031775264,0.18838538,0.00021616701],"about_ca_topic_score_codex":0.009057443,"about_ca_topic_score_gemma":0.06353981,"teacher_disagreement_score":0.8504699,"about_ca_system_score_codex":0.00016764531,"about_ca_system_score_gemma":0.0020934802,"threshold_uncertainty_score":0.99945444},"labels":[],"label_agreement":null},{"id":"W3112370274","doi":"10.23889/ijpds.v5i5.1474","title":"The Association Between Mode of Delivery and Later Educational Outcomes","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"First Nations Health and Social Secretariat of Manitoba; University of Manitoba","funders":"","keywords":"Context (archaeology); Medicine; Medical prescription; Health care; Commission; Population; Corporate governance; Demography; Political science; Environmental health; Economic growth; Geography; Nursing; Sociology; Business; Economics","score_opus":0.14623868785135002,"score_gpt":0.5185666352305915,"score_spread":0.3723279473792415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112370274","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74308866,0.00010464283,0.0014959304,0.24883492,0.0041657453,0.00045654087,0.0011619616,0.000019766558,0.0006718516],"genre_scores_gemma":[0.9914117,0.00015139394,0.0016785054,0.0051944912,0.0008738374,0.0000082598435,0.00026249397,0.0000064540627,0.00041288516],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99818474,0.00007685912,0.00058929244,0.00018359208,0.0007490378,0.00021646854],"domain_scores_gemma":[0.9967123,0.0015432676,0.0006124783,0.00016191612,0.00083960465,0.00013040996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014578714,0.00006558165,0.00013504399,0.00008798587,0.0010951776,0.000072276795,0.0009857519,0.00004781662,0.000039768624],"category_scores_gemma":[0.0027048378,0.00004479913,0.000033166227,0.00012706655,0.00006225968,0.0011923027,0.00035251447,0.00023159005,0.000010450097],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027458409,0.000005191979,0.9775111,0.000010626801,0.00003586377,1.1457289e-7,0.00030632826,0.000009333134,0.00006270712,0.0043234434,0.013450349,0.0042574923],"study_design_scores_gemma":[0.00039069564,0.00001907872,0.94649285,0.0000149817515,0.000018739938,9.0777223e-7,0.00012935323,0.0013064053,0.000009358947,0.0038907528,0.047672465,0.00005437929],"about_ca_topic_score_codex":0.00016605476,"about_ca_topic_score_gemma":0.00009416679,"teacher_disagreement_score":0.24832304,"about_ca_system_score_codex":0.00036709697,"about_ca_system_score_gemma":0.0008827706,"threshold_uncertainty_score":0.84233314},"labels":[],"label_agreement":null},{"id":"W3112385059","doi":"10.23889/ijpds.v5i5.1493","title":"Introducing Health Data Research Network Canada (HDRN Canada): A New Organization to Advance Canadian And International Population Data Science","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Canadian Institute for Health Information; University of British Columbia","funders":"","keywords":"Listing (finance); Analytics; Indigenous; Data collection; Business; Public relations; Political science; Data science; Computer science; Sociology; Finance","score_opus":0.27992938461530437,"score_gpt":0.5332584579947132,"score_spread":0.2533290733794088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112385059","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02054216,0.0005078932,0.021389324,0.9195338,0.023765648,0.0021639457,0.01153152,0.0000703079,0.00049541146],"genre_scores_gemma":[0.87390566,0.00037937754,0.026839413,0.06987964,0.007204005,0.000008478355,0.021332162,0.00005100882,0.0004002271],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9932873,0.00019052302,0.0010822404,0.0013676486,0.0028497083,0.0012225725],"domain_scores_gemma":[0.9929397,0.00041694203,0.00055867276,0.0016623443,0.0024806403,0.0019417084],"candidate_categories":["metaresearch","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.007863138,0.00018214375,0.0002690029,0.00051653915,0.004795446,0.00043807292,0.009433685,0.000054652817,0.00015623405],"category_scores_gemma":[0.0148011055,0.00018360073,0.000008045745,0.0021207558,0.000122616,0.0063157226,0.005255218,0.0007371327,0.000007465533],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.000057391735,0.000006949693,0.22178209,0.000028475602,0.000018326195,0.000007880702,0.00034799124,0.0018377423,0.000026832391,0.002707633,0.74743384,0.025744822],"study_design_scores_gemma":[0.00046050214,0.000033495828,0.3089457,0.00012321825,0.000007251259,0.000023861034,0.00050234963,0.054232705,9.2137117e-7,0.00027886571,0.6351709,0.00022026384],"about_ca_topic_score_codex":0.9974519,"about_ca_topic_score_gemma":0.99961966,"teacher_disagreement_score":0.8533635,"about_ca_system_score_codex":0.007749192,"about_ca_system_score_gemma":0.09269318,"threshold_uncertainty_score":0.9965002},"labels":[],"label_agreement":null},{"id":"W3112404225","doi":"10.23889/ijpds.v5i5.1442","title":"Leveraging Health Administrative Data to Investigate Maternal Vulnerabilities in Early Life Respiratory Syncytial Virus (RSV) Hospitalizations in Ontario, Canada","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Adolescent and Pediatric Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Children's Hospital of Eastern Ontario; University of Toronto","funders":"","keywords":"Medicine; Population; Pediatrics; Environmental health","score_opus":0.3921465288232442,"score_gpt":0.4928355795137115,"score_spread":0.1006890506904673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112404225","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9655934,0.000047287955,0.001678791,0.027427552,0.0026079784,0.0007874199,0.0017963113,0.000017687962,0.00004355477],"genre_scores_gemma":[0.9838816,0.000013354868,0.0014323547,0.012992971,0.0008339458,0.000018667526,0.0007621215,0.000014168426,0.000050818555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99624115,0.00030233755,0.0012532682,0.00061064307,0.0010565963,0.0005360008],"domain_scores_gemma":[0.99768066,0.00021417618,0.0004938296,0.00045097465,0.00041518515,0.00074519357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024184508,0.00015150968,0.00024847907,0.0003336773,0.00074338756,0.00012909542,0.0023818493,0.000057665024,0.000119011296],"category_scores_gemma":[0.0034008012,0.00015181168,0.000016021213,0.0005204595,0.00006411536,0.0020715976,0.0007824019,0.00079837115,0.000008073451],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009849156,0.000017169512,0.983099,0.000030252499,0.000005454727,0.000014280707,0.004953608,0.0006914585,0.0000123458785,0.00048727763,0.010229004,0.00036166667],"study_design_scores_gemma":[0.0006640941,0.00008060385,0.97290605,0.0002259279,0.0000027402675,0.0000022654965,0.0013789596,0.0056153615,0.0000022656125,0.00019182314,0.018772827,0.00015706291],"about_ca_topic_score_codex":0.9259145,"about_ca_topic_score_gemma":0.98491466,"teacher_disagreement_score":0.05900017,"about_ca_system_score_codex":0.002222018,"about_ca_system_score_gemma":0.020912107,"threshold_uncertainty_score":0.9846384},"labels":[],"label_agreement":null},{"id":"W3112421027","doi":"10.23889/ijpds.v5i5.1591","title":"Prescription Benzodiazepine Use During Pregnancy and Risk of Attention-Deficit/Hyperactivity Disorder in Offspring","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal Mental Health During Pregnancy and Postpartum","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health","funders":"","keywords":"Offspring; Attention deficit hyperactivity disorder; Pregnancy; Medicine; Confounding; Hazard ratio; Medical prescription; Population; Proportional hazards model; Psychiatry; Pediatrics; Obstetrics; Demography; Internal medicine; Environmental health; Confidence interval","score_opus":0.0636460692248994,"score_gpt":0.35955253296776596,"score_spread":0.29590646374286655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112421027","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99693793,0.00020810298,0.0011914792,0.0006424627,0.00050968427,0.00028218448,0.00020944868,0.00000978964,0.000008902929],"genre_scores_gemma":[0.99666876,0.00085904344,0.0022231718,0.000025043633,0.000099498786,0.0000051736265,0.00008041492,0.0000068914787,0.000032006683],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99869984,0.00002999968,0.0004095775,0.00026127716,0.0004523568,0.00014693117],"domain_scores_gemma":[0.9991889,0.000052209576,0.0003049029,0.00015453329,0.00017244894,0.00012702728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002986081,0.000077552686,0.00013707594,0.00017377362,0.0001425598,0.00007843138,0.0002736182,0.000026001026,0.000013720519],"category_scores_gemma":[0.0007969315,0.00007083668,0.000028161616,0.00014391568,0.000054625183,0.0021626076,0.0001778827,0.0001661003,0.000001096311],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003022573,0.0000628337,0.99259347,0.00022549971,0.000014759998,0.000008246814,0.00005880975,0.00014267217,0.003850786,0.0001245257,8.8400674e-7,0.0026152695],"study_design_scores_gemma":[0.0011392641,0.0000729183,0.98282284,0.001897941,0.000020710679,0.000083569306,0.000027859716,0.013492841,0.0002943001,0.000045156194,0.00004140549,0.00006119107],"about_ca_topic_score_codex":0.00046795682,"about_ca_topic_score_gemma":0.00006743079,"teacher_disagreement_score":0.013350169,"about_ca_system_score_codex":0.00006406523,"about_ca_system_score_gemma":0.00004582265,"threshold_uncertainty_score":0.2888636},"labels":[],"label_agreement":null},{"id":"W3112490717","doi":"10.23889/ijpds.v5i5.1532","title":"Characterizing Potential Medication Related Harm in the 30-Days Following Hospitalization Using Linked Provincial Administrative Health Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Trillium Health Centre; University of Toronto","funders":"","keywords":"Medicine; Emergency medicine; Emergency department; Retrospective cohort study; Logistic regression; Polypharmacy; Cohort; Adverse effect; Health care; Intensive care medicine; Internal medicine; Psychiatry","score_opus":0.17145785570745242,"score_gpt":0.45399548703706494,"score_spread":0.2825376313296125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112490717","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8578139,0.0004225565,0.049922723,0.08329624,0.0060109873,0.0013549292,0.001016121,0.0000514505,0.0001110895],"genre_scores_gemma":[0.99063313,0.0001583413,0.002582881,0.0018406907,0.000885766,0.000004159033,0.003881408,0.000008824933,0.00000480144],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976047,0.0000670039,0.0006512354,0.00041899952,0.0010598295,0.00019822759],"domain_scores_gemma":[0.9987419,0.000040723422,0.00047648238,0.00033144487,0.00030057732,0.00010885097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019448554,0.000105922176,0.00016385126,0.00014635861,0.00050780625,0.00016927981,0.0014135641,0.000036781636,0.000019855426],"category_scores_gemma":[0.0021966742,0.0000810455,0.00004546931,0.00040885023,0.00008334571,0.0023528044,0.00032612646,0.00023028823,0.0000020551302],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002338633,0.0021911159,0.5623532,0.00055568997,0.0019435721,0.00091234606,0.07903276,0.0021135334,0.11351422,0.02275284,0.03763202,0.17466007],"study_design_scores_gemma":[0.002804744,0.00050655263,0.3693808,0.0005802687,0.00018561848,0.00029368256,0.004825572,0.6131003,0.000097596225,0.0006877221,0.0071747308,0.00036243515],"about_ca_topic_score_codex":0.000107735854,"about_ca_topic_score_gemma":0.000025713285,"teacher_disagreement_score":0.61098677,"about_ca_system_score_codex":0.00015961795,"about_ca_system_score_gemma":0.00058712106,"threshold_uncertainty_score":0.39056864},"labels":[],"label_agreement":null},{"id":"W3112495257","doi":"10.23889/ijpds.v5i5.1630","title":"Using A Privacy Preserving Record Linkage to Facilitate an Ongoing Crosswalk Between Research and Health Administrative Databases","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Indoc Research; Ontario Brain Institute","funders":"","keywords":"Schema crosswalk; Record linkage; Computer science; Database; Data science; Medicine; Engineering; Transport engineering","score_opus":0.9620375251486527,"score_gpt":0.6997589936175305,"score_spread":0.26227853153112224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112495257","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55038255,0.000029195131,0.41243318,0.03141327,0.0007527528,0.00064069737,0.0042253565,0.000026434327,0.00009657463],"genre_scores_gemma":[0.8905129,0.000019975894,0.10703528,0.0011638659,0.00057413947,0.000004887301,0.00054840563,0.000008624085,0.00013192165],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99387455,0.00030454126,0.0009861472,0.0009948392,0.0034317377,0.00040820095],"domain_scores_gemma":[0.9958295,0.0008576331,0.00044397207,0.00084303867,0.0013327054,0.00069310213],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.021981489,0.00011791595,0.00021560787,0.0006036862,0.0013384413,0.0034561467,0.0053279195,0.00001976947,0.000057955593],"category_scores_gemma":[0.015780296,0.00010077675,0.000026879168,0.0010934761,0.00023583314,0.009811196,0.0037419193,0.00026150877,0.000018037264],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062090537,0.00029512882,0.29133326,0.0000806471,0.000113946706,0.000045312154,0.017799294,0.002245883,0.0020172326,0.032212608,0.044714972,0.6085208],"study_design_scores_gemma":[0.0012413814,0.0014323189,0.35350972,0.0003467447,0.000015435553,0.000047048117,0.008528743,0.17979741,0.00022448356,0.03845972,0.41580352,0.0005934722],"about_ca_topic_score_codex":0.0015172221,"about_ca_topic_score_gemma":0.00062790053,"teacher_disagreement_score":0.6079273,"about_ca_system_score_codex":0.00017502453,"about_ca_system_score_gemma":0.0004596198,"threshold_uncertainty_score":0.9999617},"labels":[],"label_agreement":null},{"id":"W3112538871","doi":"10.23889/ijpds.v5i5.1647","title":"Evaluating Full Day Kindergarten – Is It Associated with Improved Short- And Long-Term Education Outcomes Among Metis Children?","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Winnipeg; Government of Manitoba; University of Manitoba; Manitoba Health","funders":"","keywords":"Metis; Numeracy; Population; Cohort; Demography; Graduation (instrument); Medicine; Psychology; Literacy; Environmental health; Pedagogy; Database; Sociology","score_opus":0.0921120617224014,"score_gpt":0.44385699827599756,"score_spread":0.3517449365535962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112538871","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9896416,0.0000460157,0.0019069621,0.005518775,0.0016488142,0.00067705393,0.00013311942,0.000029648121,0.00039798472],"genre_scores_gemma":[0.99554974,0.00022261868,0.0016654248,0.00071328285,0.00079724775,0.000004915789,0.00052782724,0.000012970022,0.0005059998],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99724936,0.00014778116,0.00045842785,0.0004862337,0.0013011366,0.00035705682],"domain_scores_gemma":[0.99764204,0.00016766843,0.00045836778,0.00021424021,0.0011740101,0.0003436859],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002914964,0.0001383897,0.00016210417,0.00021086601,0.0042957976,0.0007855302,0.0012408269,0.000072054776,0.00011655035],"category_scores_gemma":[0.0005007289,0.000109151464,0.00003909399,0.00038476542,0.0003190159,0.0031622194,0.000023266573,0.0001875731,0.0000033882802],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003257157,0.00012677538,0.9488911,0.000005497646,0.000095820214,8.262558e-7,0.038338747,0.0000253051,0.000034393106,0.0035183034,0.00027668706,0.008653966],"study_design_scores_gemma":[0.00036579432,0.000120656965,0.99229765,0.000069189824,0.00005546651,0.0000123087475,0.00085295574,0.0037408015,0.000016100428,0.0003224568,0.0019410473,0.00020554698],"about_ca_topic_score_codex":0.006109735,"about_ca_topic_score_gemma":0.10662287,"teacher_disagreement_score":0.10051314,"about_ca_system_score_codex":0.00033745012,"about_ca_system_score_gemma":0.006154978,"threshold_uncertainty_score":0.9994792},"labels":[],"label_agreement":null},{"id":"W3112621162","doi":"10.23889/ijpds.v5i5.1636","title":"Measuring Community Strengths – Using Data from The First Nations Regional Health Survey Linked with A Whole-Population Administrative Data Repository","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; First Nations Health and Social Secretariat of Manitoba; Manitoba Health","funders":"","keywords":"Strengths and weaknesses; Construct (python library); Community health; Population; Survey data collection; Psychology; Gerontology; Public health; Environmental health; Medicine; Social psychology; Nursing; Statistics; Computer science","score_opus":0.4430040552314347,"score_gpt":0.47005309852812,"score_spread":0.027049043296685282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112621162","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8881968,0.00040410546,0.027978182,0.041584432,0.007190271,0.0025867275,0.03091052,0.00015851787,0.000990406],"genre_scores_gemma":[0.9613619,0.00034768027,0.005957289,0.00045458638,0.002064002,0.0000015017633,0.029747568,0.00001507224,0.00005042875],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9954977,0.0009237427,0.00071441225,0.0006334594,0.0018603997,0.00037025733],"domain_scores_gemma":[0.9939869,0.0018740125,0.0010449192,0.0015653815,0.0012017774,0.00032698805],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.007760648,0.00015544347,0.0001841325,0.00015117564,0.024404032,0.0010903142,0.008100821,0.00006509122,0.000015373762],"category_scores_gemma":[0.001497193,0.0001164537,0.000024292247,0.0007406249,0.000471971,0.005774244,0.00018216304,0.0004963645,0.000003580776],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009927151,0.0012065471,0.61928576,0.00007945452,0.00058652944,0.000014219925,0.30803874,0.0053659226,0.000031824417,0.043462493,0.016902909,0.00403284],"study_design_scores_gemma":[0.0007918995,0.00012534249,0.63964576,0.0003497138,0.000057091413,0.0000437081,0.009016853,0.070311055,0.000003387558,0.00061452953,0.2786348,0.00040583988],"about_ca_topic_score_codex":0.4681479,"about_ca_topic_score_gemma":0.94352436,"teacher_disagreement_score":0.47537646,"about_ca_system_score_codex":0.00059555186,"about_ca_system_score_gemma":0.013458167,"threshold_uncertainty_score":0.99994665},"labels":[],"label_agreement":null},{"id":"W3112659431","doi":"10.23889/ijpds.v5i5.1449","title":"Linking Health and Social Data to Assess the Performance of High Dimensional Propensity Scores","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"","keywords":"Propensity score matching; Confounding; Medicine; Demography; Social deprivation; Matching (statistics); Environmental health; Psychology","score_opus":0.23565191836803684,"score_gpt":0.4298236471267988,"score_spread":0.19417172875876199,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112659431","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9444401,0.000030610056,0.00056570536,0.053879574,0.0004890981,0.00021621917,0.00036779474,0.000006430192,0.000004419678],"genre_scores_gemma":[0.9872864,0.000029866087,0.0037285006,0.007942249,0.0005501006,7.0001005e-7,0.00044984618,0.0000037645973,0.000008586797],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984535,0.00002169961,0.00031414017,0.00025541935,0.0008132843,0.00014198056],"domain_scores_gemma":[0.9989902,0.00003007412,0.00022425635,0.0002144645,0.00036344636,0.00017757509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001028635,0.00006029258,0.00013776748,0.00005746433,0.00042355192,0.00009463533,0.0010859146,0.0000141441915,0.000006610488],"category_scores_gemma":[0.0002852016,0.00003829181,0.000012700021,0.00013542088,0.00009363143,0.000785227,0.00086010515,0.00013272052,0.0000019142383],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012810753,0.00010404336,0.93731576,0.00021184604,0.00006062441,0.000007215957,0.0008935875,0.00042162827,0.0024249174,0.006710697,0.0071463035,0.043422323],"study_design_scores_gemma":[0.00052464625,0.00026732005,0.9567662,0.00017989207,0.000012102183,0.00016306508,0.000048571637,0.037767354,0.00009236565,0.00013951109,0.0039782524,0.000060716953],"about_ca_topic_score_codex":0.00022372337,"about_ca_topic_score_gemma":0.000023555462,"teacher_disagreement_score":0.045937326,"about_ca_system_score_codex":0.000051173727,"about_ca_system_score_gemma":0.0003669982,"threshold_uncertainty_score":0.32576618},"labels":[],"label_agreement":null},{"id":"W3112687805","doi":"10.23889/ijpds.v5i5.1463","title":"Do Home Adaptations Prevent Falls for Older People?","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Economic and Social Research Council","keywords":"Medicine; Logistic regression; Odds ratio; Gerontology; Confidence interval; Demography; Quarter (Canadian coin); Odds; Fall prevention; Injury prevention; Poison control; Medical emergency; Geography; Internal medicine","score_opus":0.13489570896654915,"score_gpt":0.43238831562196856,"score_spread":0.29749260665541943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112687805","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3635065,0.0003383207,0.5463682,0.07543577,0.006365405,0.0034764414,0.002666729,0.00017323474,0.0016694209],"genre_scores_gemma":[0.9867684,0.00004612674,0.010167489,0.0008050733,0.0007882144,0.00002826502,0.0011695838,0.000011727483,0.00021512182],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9982928,0.000008659261,0.00034188494,0.00035155815,0.00081768946,0.00018742705],"domain_scores_gemma":[0.99873865,0.00006929534,0.00019781971,0.00025481335,0.0005290468,0.00021035415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046243815,0.000091816226,0.00012077748,0.00017760902,0.00022766495,0.00038951423,0.0009385419,0.00001917451,0.00017930903],"category_scores_gemma":[0.00080046203,0.00008237674,0.00007587019,0.000245624,0.000058470298,0.0016242596,0.00021351015,0.00007782692,0.000011671569],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025091213,0.0018984273,0.102663286,0.0006886681,0.0013701324,0.0000726701,0.005395308,0.018248077,0.0066301436,0.3827431,0.22255312,0.25522792],"study_design_scores_gemma":[0.0053605773,0.00034870364,0.6700403,0.00025502022,0.0002884414,0.00011107813,0.0014095455,0.2399421,0.00007568925,0.008103357,0.073688306,0.00037689408],"about_ca_topic_score_codex":0.00001702384,"about_ca_topic_score_gemma":0.00002123794,"teacher_disagreement_score":0.6232619,"about_ca_system_score_codex":0.00015280671,"about_ca_system_score_gemma":0.00033022658,"threshold_uncertainty_score":0.37560946},"labels":[],"label_agreement":null},{"id":"W3112896000","doi":"10.23889/ijpds.v5i5.1648","title":"Use of Prescription Opioids and Impact of Replacing Oxycontin With Oxyneo On Opioid Use Among Metis Citizens, 2013-2018","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Metis; Medical prescription; Medicine; Opioid; Pharmacoepidemiology; Pharmacology; Internal medicine; Database","score_opus":0.08755337834508321,"score_gpt":0.3629176030505642,"score_spread":0.275364224705481,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112896000","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952406,0.00004092834,0.0028737884,0.00059507054,0.00024662423,0.00037788696,0.00060206006,0.000011914356,0.000011120189],"genre_scores_gemma":[0.9881556,0.00013257505,0.011061648,0.000089455774,0.00009443524,0.0000037498755,0.00040271622,0.00001267083,0.000047138547],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982225,0.000024710946,0.00044897693,0.00033550113,0.0008205747,0.00014776085],"domain_scores_gemma":[0.99840474,0.000103002945,0.0004713079,0.000317842,0.0005299656,0.0001731605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003248281,0.00012562842,0.00022295422,0.0002732437,0.00008892297,0.00016540714,0.000332408,0.00003275274,0.000022365693],"category_scores_gemma":[0.0010427928,0.00009128168,0.00006230041,0.00022392572,0.0001692954,0.002272557,0.00012984588,0.000109335335,6.5294887e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012926941,0.00013703677,0.9781069,0.00003513466,0.0001964649,0.000010422401,0.00052443374,0.0014226068,0.012175156,0.00031897993,0.0019403603,0.0038398188],"study_design_scores_gemma":[0.0013794784,0.0010418849,0.9671222,0.00033651703,0.000089373505,0.00006757736,0.000077124016,0.027727976,0.0016642439,0.00006162826,0.00033806305,0.00009394544],"about_ca_topic_score_codex":0.0016502131,"about_ca_topic_score_gemma":0.000041523333,"teacher_disagreement_score":0.02630537,"about_ca_system_score_codex":0.0001332308,"about_ca_system_score_gemma":0.00016628373,"threshold_uncertainty_score":0.37223592},"labels":[],"label_agreement":null},{"id":"W3112904752","doi":"10.23889/ijpds.v5i5.1420","title":"Creation of First Nations Health Profiles Through Data Linkage in Manitoba","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"First Nations Health and Social Secretariat of Manitoba","funders":"","keywords":"Mandate; Information governance; Data sharing; Political science; Business; Public administration; Medicine; Information system; Law","score_opus":0.5272190626369835,"score_gpt":0.5404742119118103,"score_spread":0.01325514927482685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112904752","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04306562,0.00023873041,0.7709506,0.15970328,0.0053757876,0.0016289792,0.01665997,0.00006051831,0.0023164863],"genre_scores_gemma":[0.9631613,0.00020582236,0.03152837,0.0011492004,0.0003728579,0.000006114897,0.0035119331,0.000006833351,0.000057602516],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.995095,0.000111367284,0.0012701707,0.00067747594,0.0026452993,0.00020069329],"domain_scores_gemma":[0.996353,0.0007138664,0.0009687246,0.0010949759,0.00074680225,0.00012264041],"candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.007773942,0.00009482189,0.00019709184,0.00053735415,0.00045927532,0.00071865926,0.008311358,0.000026817766,0.00009049769],"category_scores_gemma":[0.019612953,0.000079887606,0.000034151653,0.0013302072,0.00016295459,0.009043418,0.0019667782,0.00012931888,0.00002294783],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000366525,0.00079916924,0.22837152,0.00014361067,0.00010986884,0.000018534543,0.005268225,0.011937089,0.0002528887,0.36368147,0.16863164,0.22041947],"study_design_scores_gemma":[0.0013488926,0.00016188336,0.16047913,0.00022215798,0.000014896205,0.000021566411,0.0038597237,0.32172504,0.000091517184,0.032076642,0.4797164,0.0002821517],"about_ca_topic_score_codex":0.0010700045,"about_ca_topic_score_gemma":0.0077034817,"teacher_disagreement_score":0.9200956,"about_ca_system_score_codex":0.00013308156,"about_ca_system_score_gemma":0.00027627253,"threshold_uncertainty_score":0.99705416},"labels":[],"label_agreement":null},{"id":"W3112907032","doi":"10.23889/ijpds.v5i5.1425","title":"Maternal Depression in Early Childhood and Developmental Vulnerability at School Entry","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal Mental Health During Pregnancy and Postpartum","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Depression (economics); Vulnerability (computing); Early childhood; Child development; Population; Demography; Medicine; Psychology; Developmental psychology; Cohort; Pediatrics; Environmental health","score_opus":0.050136411000951654,"score_gpt":0.3655630415503555,"score_spread":0.31542663054940384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112907032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969077,0.00009494411,0.00016888739,0.0016664828,0.00067641214,0.0002620648,0.00010467314,0.000014122113,0.00010472229],"genre_scores_gemma":[0.99584454,0.00007285269,0.0028852317,0.0007676813,0.00025230786,0.000005966258,0.000091461414,0.000006714448,0.00007326885],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984593,0.000021563492,0.00038975463,0.00033589773,0.00059986516,0.0001936345],"domain_scores_gemma":[0.99926674,0.000034608194,0.00013481872,0.00011760101,0.00009408591,0.00035214607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049408973,0.00008942841,0.000117573494,0.00011971726,0.0002194293,0.0001234258,0.00045595053,0.000031970456,0.000110291265],"category_scores_gemma":[0.00048068282,0.00007563984,0.000019436273,0.00010081017,0.000060043847,0.0010997701,0.00041619496,0.00018408298,0.000017611004],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046043034,0.000032907086,0.99566513,0.000050484905,0.0000069324738,0.000021472977,0.00026401647,0.00000972416,0.0006436891,0.000038326652,0.000059582395,0.002747286],"study_design_scores_gemma":[0.0012535478,0.0000653784,0.99382824,0.0005589946,0.00000539888,0.00053720555,0.000026841304,0.0014611126,0.0015808584,0.00012401082,0.00048405066,0.000074341166],"about_ca_topic_score_codex":0.00011612259,"about_ca_topic_score_gemma":0.000019221463,"teacher_disagreement_score":0.0027163443,"about_ca_system_score_codex":0.00025434303,"about_ca_system_score_gemma":0.00013857438,"threshold_uncertainty_score":0.3084503},"labels":[],"label_agreement":null},{"id":"W3112907461","doi":"10.23889/ijpds.v5i5.1434","title":"Benzodiazepine Use Before Conception and Risk of Ectopic Pregnancy","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ectopic Pregnancy Diagnosis and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Ectopic pregnancy; Medicine; Medical prescription; Obstetrics; Pregnancy; Gynecology; Relative risk; Anxiety; Risk factor; Benzodiazepine; Internal medicine; Psychiatry; Confidence interval","score_opus":0.09968060235526824,"score_gpt":0.3811432177948323,"score_spread":0.2814626154395641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112907461","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9703488,0.0003216025,0.021929828,0.005661512,0.00086823467,0.00044351796,0.00032765022,0.000018486931,0.00008038205],"genre_scores_gemma":[0.9904627,0.0007757367,0.008003114,0.00030620265,0.00023157368,0.000004114209,0.00016273676,0.0000039680453,0.000049851682],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990394,0.00001105329,0.00026404322,0.00020544465,0.0003912503,0.00008879119],"domain_scores_gemma":[0.99918956,0.000033361517,0.00023050219,0.00016704276,0.00027780927,0.00010175486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021981243,0.000055453176,0.00010698269,0.000090366026,0.00008618392,0.00007815629,0.0003364456,0.000017665396,0.000031516454],"category_scores_gemma":[0.0011965733,0.00004507939,0.000029893512,0.000105976265,0.000092276336,0.0011011781,0.00018507065,0.000071861214,9.845819e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004771277,0.0000527949,0.89157593,0.000038090107,0.000069705915,0.0000061403002,0.00022196765,0.000057416444,0.0006762563,0.0066286027,0.0008884594,0.0997369],"study_design_scores_gemma":[0.0010801187,0.00021489768,0.9769538,0.00037942492,0.0000740463,0.000022502862,0.000033932854,0.014398392,0.0002894624,0.00084053626,0.0056553646,0.000057521225],"about_ca_topic_score_codex":0.00008975789,"about_ca_topic_score_gemma":0.000032134925,"teacher_disagreement_score":0.09967938,"about_ca_system_score_codex":0.000032229826,"about_ca_system_score_gemma":0.00004234616,"threshold_uncertainty_score":0.18382841},"labels":[],"label_agreement":null},{"id":"W3112953570","doi":"10.23889/ijpds.v5i5.1507","title":"Involving the Public in Data Linkage Research","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; University Health Network; University of British Columbia","funders":"","keywords":"Public relations; Public engagement; Data sharing; Session (web analytics); Government (linguistics); Political science; Moderation; Sociology; Psychology; Social psychology; Medicine; Business; Advertising","score_opus":0.5224479911836669,"score_gpt":0.536670488500658,"score_spread":0.0142224973169911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112953570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5258486,0.0013601125,0.013537067,0.44191915,0.0056170234,0.0019838363,0.008424508,0.00015237463,0.0011573039],"genre_scores_gemma":[0.99096286,0.00012852158,0.0029709022,0.0015253659,0.0009426298,0.000004781747,0.003408694,0.0000103309785,0.000045884626],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967064,0.00010617948,0.00042637475,0.000530074,0.0019215802,0.0003093922],"domain_scores_gemma":[0.9971624,0.00029035716,0.00015728065,0.0011865348,0.00093284197,0.00027056364],"candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.006339717,0.000075836935,0.00011859414,0.00033199697,0.00035326745,0.0006341553,0.0057768403,0.000026009822,0.000084326624],"category_scores_gemma":[0.016648145,0.000054779663,0.000023997773,0.0009495046,0.00026517795,0.0037168206,0.0023927325,0.00045351434,0.0000371732],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057273626,0.00033140308,0.73522764,0.0000624632,0.00011460986,0.00027662874,0.0006089824,0.00022774863,0.0049349293,0.02024233,0.15679117,0.080609344],"study_design_scores_gemma":[0.0012358314,0.00005878247,0.37551785,0.00013376818,0.000011003287,0.00016589284,0.00032470957,0.35205704,0.000027768425,0.0012517172,0.26908147,0.0001341519],"about_ca_topic_score_codex":0.00007959957,"about_ca_topic_score_gemma":0.00022519704,"teacher_disagreement_score":0.46511427,"about_ca_system_score_codex":0.00017227561,"about_ca_system_score_gemma":0.00064196554,"threshold_uncertainty_score":0.9996024},"labels":[],"label_agreement":null},{"id":"W3112960436","doi":"10.23889/ijpds.v5i5.1431","title":"An Evaluation of Linked Administrative Data for Cancer Clinical Trial Economic Analysis","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; University of Ottawa; Canadian Agency for Drugs and Technologies in Health; Canada Research Chairs; Queen's University","funders":"","keywords":"Medicine; Cetuximab; Clinical trial; Economic evaluation; Randomized controlled trial; Colorectal cancer; Health care; Cancer; Family medicine; Internal medicine","score_opus":0.9110677057298132,"score_gpt":0.6893844954414305,"score_spread":0.22168321028838267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112960436","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69563276,0.0003611913,0.19859046,0.043693297,0.009036885,0.0030436497,0.04948922,0.000030525724,0.00012200734],"genre_scores_gemma":[0.97125,0.00007326017,0.018636448,0.0017315894,0.0028906167,0.000070066504,0.0053205485,0.000014278078,0.000013204653],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9933523,0.000282368,0.004690249,0.0009860002,0.00046435758,0.00022473466],"domain_scores_gemma":[0.9920837,0.0009029383,0.00480522,0.0010598741,0.0008623561,0.00028586682],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.056673944,0.00012806109,0.0006819558,0.0004595287,0.00026161424,0.00033612645,0.003592609,0.000084794905,0.00032829645],"category_scores_gemma":[0.018861754,0.00014891046,0.00015765785,0.00030009876,0.00014455862,0.0046327813,0.0002347682,0.0001307007,0.00002335152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.016062567,0.0014117197,0.5362375,0.00018665665,0.0062227817,0.0000011399321,0.0030794991,0.16053861,0.000072938,0.17792085,0.054015063,0.04425067],"study_design_scores_gemma":[0.0077356556,0.00026005,0.03882397,0.000013216794,0.00018218835,0.0000010528755,0.00020580608,0.93739957,0.000002841435,0.0050285626,0.010186476,0.00016059994],"about_ca_topic_score_codex":0.00061849784,"about_ca_topic_score_gemma":0.0007102059,"teacher_disagreement_score":0.77686095,"about_ca_system_score_codex":0.00050766364,"about_ca_system_score_gemma":0.0014072724,"threshold_uncertainty_score":0.9894028},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"}],"label_agreement":"agree"},{"id":"W3112979811","doi":"10.23889/ijpds.v5i5.1529","title":"Building A Research Partnership Between Computer Scientists and Health Service Researchers for Access and Analysis of Population-Level Health Datasets","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Vector Institute; Hospital for Sick Children","funders":"","keywords":"General partnership; Population; Timeline; Computer science; Data science; Data access; Population health; Data sharing; Knowledge management; Public relations; Political science; Medicine; Environmental health","score_opus":0.9001140944178496,"score_gpt":0.7039699978539685,"score_spread":0.1961440965638811,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112979811","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7368858,0.00021068788,0.1121272,0.14562884,0.0005448869,0.0012438939,0.0033382624,0.000016967148,0.000003455201],"genre_scores_gemma":[0.95837855,0.000085589825,0.034162927,0.0018009456,0.00051038037,0.000008515389,0.005040895,0.00000802492,0.0000041951803],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971107,0.00010562714,0.0007307205,0.0005214634,0.0011748907,0.0003565723],"domain_scores_gemma":[0.9968,0.00050632516,0.00040044563,0.00027971424,0.0014430966,0.0005704402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00830933,0.000082823164,0.00028206364,0.0009873346,0.00074438803,0.00042067777,0.0008358237,0.000036327878,0.0000075835815],"category_scores_gemma":[0.0018241967,0.00007711049,0.000033935128,0.0017986734,0.00018184802,0.0015420844,0.0004101641,0.00020940516,4.1442175e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020867938,0.000058667898,0.74009365,0.0002917543,0.00018238659,8.3116106e-7,0.0014749933,0.0005489918,0.000070006834,0.0036725271,0.0051173395,0.2482802],"study_design_scores_gemma":[0.00017201682,0.00025354564,0.755226,0.00016077224,0.000047726928,0.000010435161,0.00022400208,0.24003103,0.000045277524,0.0017502988,0.0020056255,0.000073215815],"about_ca_topic_score_codex":0.005544203,"about_ca_topic_score_gemma":0.000871885,"teacher_disagreement_score":0.24820697,"about_ca_system_score_codex":0.00026099238,"about_ca_system_score_gemma":0.0007756444,"threshold_uncertainty_score":0.83812135},"labels":[],"label_agreement":null},{"id":"W3113007096","doi":"10.23889/ijpds.v5i5.1543","title":"Transformation of Data Access Models In BC","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Scientific Research and Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Timeline; Provisioning; Computer science; Data access; Data management; Database; Data science; Operating system; Statistics","score_opus":0.3386497578390779,"score_gpt":0.4705729874426805,"score_spread":0.1319232296036026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113007096","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021169791,0.000022337392,0.9665974,0.010751562,0.00080737204,0.00016774167,0.0002266186,0.000025479661,0.00023172388],"genre_scores_gemma":[0.96035147,0.00003926222,0.0391455,0.00014716326,0.0000654314,0.0000021325884,0.00024052364,0.0000023717562,0.0000061423557],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99778134,0.000023398257,0.00044079564,0.0004431724,0.0011114895,0.0001998182],"domain_scores_gemma":[0.99843955,0.000060519313,0.00019965191,0.0007832141,0.00040678756,0.00011025632],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0019948944,0.00005820205,0.000093036535,0.0004971209,0.00011368515,0.0006508269,0.017786419,0.000026658216,0.000010532544],"category_scores_gemma":[0.00070465804,0.000051608025,0.000018272138,0.0010293869,0.00011480589,0.024292557,0.0021224401,0.00013452831,0.0000032846876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001129416,0.00015203064,0.007091348,0.000027357573,0.000028965029,0.000017450187,0.0010005113,0.015781669,0.0040302477,0.41065922,0.004746005,0.55635226],"study_design_scores_gemma":[0.00032685438,0.000024644187,0.0034097242,0.000014391659,8.572271e-7,0.000016633947,0.000023749026,0.96924293,0.0005276172,0.024065102,0.0022924566,0.00005506803],"about_ca_topic_score_codex":0.0001378738,"about_ca_topic_score_gemma":0.00006242539,"teacher_disagreement_score":0.9534612,"about_ca_system_score_codex":0.000049830687,"about_ca_system_score_gemma":0.00025406462,"threshold_uncertainty_score":0.98935413},"labels":[],"label_agreement":null},{"id":"W3113062503","doi":"10.23889/ijpds.v5i5.1581","title":"Supporting Drug Regulators Through Simple Rapid Cycle Analyses","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Outcome (game theory); Event (particle physics); Duration (music); Medicine; Operations research; Computer science; Medical emergency; Process management; Data science; Business; Engineering","score_opus":0.6235666732587184,"score_gpt":0.5768261164931058,"score_spread":0.04674055676561262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113062503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59030485,0.0009615793,0.20668583,0.18830663,0.0065834727,0.0009876525,0.0041329702,0.00014596122,0.0018910636],"genre_scores_gemma":[0.96974236,0.00004770689,0.017107777,0.011055964,0.0013636627,0.00000860091,0.0005720516,0.000018833112,0.00008303555],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954483,0.000078847435,0.003048422,0.00065396156,0.00040099383,0.000369465],"domain_scores_gemma":[0.99579245,0.00035360566,0.002837471,0.00045755334,0.0003019124,0.00025700624],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.011568123,0.00013438363,0.00040384478,0.00028171513,0.0005624154,0.0005433737,0.002010582,0.000041280724,0.0005058123],"category_scores_gemma":[0.011724736,0.00015495362,0.00010479412,0.00037624448,0.00010898979,0.0056868866,0.00029226736,0.00015335315,0.00020551388],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013766688,0.00020088481,0.3045358,0.00015762853,0.00038479952,0.000010315662,0.0071577425,0.024751415,0.00035963563,0.31506756,0.34112677,0.006109807],"study_design_scores_gemma":[0.0014369217,0.000080830236,0.060815915,0.00006498226,0.000020771888,0.000051246734,0.0020252261,0.53167975,0.0001412355,0.10624796,0.29681692,0.0006182183],"about_ca_topic_score_codex":0.00058879866,"about_ca_topic_score_gemma":0.000044449367,"teacher_disagreement_score":0.5069283,"about_ca_system_score_codex":0.00035465066,"about_ca_system_score_gemma":0.00021339521,"threshold_uncertainty_score":0.9965999},"labels":[],"label_agreement":null},{"id":"W3113107554","doi":"10.23889/ijpds.v5i5.1439","title":"Estimating the Proportion of Antibiotics Attributable to Common Paediatric Respiratory Viruses: An Example Leveraging Unique Population-Based Prescribing and Laboratory Data","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Respiratory viral infections research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Medical prescription; Antibiotics; Population; Antibiotic resistance; Pediatrics; Amoxicillin; Respiratory tract infections; Epidemiology; Internal medicine; Respiratory system; Environmental health; Biology; Microbiology","score_opus":0.3311997712027876,"score_gpt":0.46418549896829353,"score_spread":0.13298572776550593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113107554","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9388387,0.000047591155,0.058772556,0.00085433014,0.00038470546,0.0006231819,0.00044181122,0.000031710508,0.0000053766385],"genre_scores_gemma":[0.97663724,0.0000025085035,0.020738272,0.0016722074,0.00040976627,0.000001865877,0.0005196999,0.000016822532,0.0000016389539],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99725467,0.00013208737,0.0006663085,0.0005070069,0.0012210595,0.00021886452],"domain_scores_gemma":[0.9972013,0.0001716752,0.00040957268,0.0008222665,0.0011312969,0.0002638779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036608349,0.000116825555,0.00018940198,0.000380554,0.0005628713,0.00037725488,0.0013948258,0.000043143526,0.000013397242],"category_scores_gemma":[0.0040150126,0.00009328999,0.00002135063,0.0009049236,0.0001181155,0.002956862,0.00061123644,0.00027164517,0.000001590499],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015120053,0.00007567745,0.94970584,0.000055782748,0.00002208517,0.0000060855677,0.00012898624,0.02264796,0.017992157,0.00041744212,0.00038016294,0.008416641],"study_design_scores_gemma":[0.000661208,0.00035764443,0.34183016,0.00012704806,0.000044105396,0.000020924503,0.00008758705,0.65047055,0.003334826,0.00014480625,0.0027779648,0.00014316059],"about_ca_topic_score_codex":0.00084700435,"about_ca_topic_score_gemma":0.000084538806,"teacher_disagreement_score":0.6278226,"about_ca_system_score_codex":0.00016803261,"about_ca_system_score_gemma":0.0005850806,"threshold_uncertainty_score":0.4806635},"labels":[],"label_agreement":null},{"id":"W3113179148","doi":"10.23889/ijpds.v5i5.1428","title":"Life expectancy and health care utilization of individuals with dementia in Ontario, Canada: A population-level study","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Palliative Care and End-of-Life Issues","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bruyère; University of Toronto; Ottawa Public Health; University of Ottawa; Ottawa Hospital; Statistics Canada","funders":"","keywords":"Dementia; Life expectancy; Medicine; Health care; Gerontology; Ambulatory care; Population; Long-term care; Inpatient care; Family medicine; Disease; Psychiatry; Environmental health","score_opus":0.3776144313518684,"score_gpt":0.4804772759735326,"score_spread":0.10286284462166423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113179148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99474967,0.00047462975,0.0019590615,0.0020045282,0.00019727698,0.0003660339,0.00022458176,0.0000036333745,0.000020570827],"genre_scores_gemma":[0.992478,0.00002875791,0.0065169074,0.00035712952,0.00006295626,0.0000032524322,0.00054366415,0.0000051204433,0.000004219661],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99829346,0.000021074742,0.00049028837,0.00022403811,0.0008614306,0.000109684916],"domain_scores_gemma":[0.9987996,0.00003230909,0.0003903917,0.00012576977,0.00047985095,0.00017203373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003556486,0.00007591105,0.0002045917,0.00018404966,0.00007899456,0.000030385454,0.00030688045,0.000014357293,0.000021354726],"category_scores_gemma":[0.0005910312,0.00006390512,0.000012736029,0.00025328726,0.000035403435,0.00056877005,0.00008983818,0.00008778179,5.5222472e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008469401,0.000044516022,0.9934211,0.00002119972,0.00004934509,0.0000030222711,0.004461477,0.00021256598,0.000012986894,0.00012815306,0.00030408285,0.0012568918],"study_design_scores_gemma":[0.0013609446,0.0002665645,0.99206555,0.00024563354,0.00002734665,0.0000069728235,0.0040036575,0.0011619956,0.000030298885,0.00001844304,0.0007559666,0.000056642788],"about_ca_topic_score_codex":0.6516492,"about_ca_topic_score_gemma":0.82688415,"teacher_disagreement_score":0.17523496,"about_ca_system_score_codex":0.00030739707,"about_ca_system_score_gemma":0.0020109627,"threshold_uncertainty_score":0.35673615},"labels":[],"label_agreement":null},{"id":"W3113358503","doi":"10.23889/ijpds.v5i5.1468","title":"Provincial Overdose Cohort: Population Data Linkage During an Overdose Crisis","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; BC Centre for Disease Control","funders":"","keywords":"Medicine; Drug overdose; Population; Medical prescription; Cohort; Declaration; Public health; Emergency medicine; Medical emergency; Poison control; Environmental health; Internal medicine","score_opus":0.07549727959997957,"score_gpt":0.4007831256439038,"score_spread":0.3252858460439242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113358503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9868155,0.00005459715,0.0025617406,0.0054492136,0.0015234564,0.0006954762,0.002780312,0.000081256556,0.000038446295],"genre_scores_gemma":[0.97410005,0.00006422214,0.008904855,0.00083810627,0.0015443356,0.000008222888,0.014479182,0.000028492062,0.00003251214],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99647623,0.00003780822,0.000638796,0.000890008,0.0016527652,0.00030438515],"domain_scores_gemma":[0.9975796,0.00003337626,0.0004038117,0.0010743265,0.00049095583,0.00041794908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072286977,0.00019438997,0.00023536857,0.00027858472,0.00045443844,0.00049473235,0.0021714384,0.000064262946,0.00009034847],"category_scores_gemma":[0.0013047943,0.00017725817,0.000058485217,0.00036864108,0.000060933944,0.00593129,0.0008986388,0.00023110044,0.000014188988],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000921582,0.00053618563,0.97999376,0.00006549747,0.00018374053,0.00009774973,0.00058843417,0.00070142106,0.0036423716,0.0009171178,0.0033876137,0.008964497],"study_design_scores_gemma":[0.0019972073,0.00017752986,0.89714396,0.000064385225,0.00013023223,0.00012345384,0.00015993291,0.09766242,0.00018370892,0.00026401813,0.0018930432,0.00020013051],"about_ca_topic_score_codex":0.0009735813,"about_ca_topic_score_gemma":0.0001178846,"teacher_disagreement_score":0.096961,"about_ca_system_score_codex":0.00038683257,"about_ca_system_score_gemma":0.00033799815,"threshold_uncertainty_score":0.7228378},"labels":[],"label_agreement":null},{"id":"W3113375788","doi":"10.23889/ijpds.v5i5.1579","title":"Maternal and Neonatal Outcomes Associated with Psychostimulant Use in Pregnancy","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal Mental Health During Pregnancy and Postpartum","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Women's College Hospital","funders":"","keywords":"Medicine; Pregnancy; Relative risk; Confidence interval; Cohort; Cohort study; Population; Obstetrics; Gestation; Pediatrics; Demography; Environmental health; Internal medicine","score_opus":0.10519102923119307,"score_gpt":0.39809312391689083,"score_spread":0.2929020946856978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113375788","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945824,0.00008215404,0.0008124972,0.0033230528,0.00060562696,0.00029863804,0.00026175205,0.000017824957,0.000016043658],"genre_scores_gemma":[0.9964573,0.000063348125,0.0022567944,0.00089776964,0.00007553626,0.0000054707903,0.0001535331,0.000008927065,0.00008135887],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99856275,0.000016455486,0.00032673366,0.0002846566,0.0006131603,0.00019626689],"domain_scores_gemma":[0.99922895,0.000073726704,0.00018020453,0.00013847635,0.0001602622,0.00021837815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027082974,0.00009671368,0.00014824021,0.00014422722,0.00011436906,0.00018831187,0.0004101395,0.00002719165,0.000021008536],"category_scores_gemma":[0.00053611473,0.00007111808,0.000018277267,0.00013152316,0.00007103445,0.0015329572,0.00012908838,0.00015463564,0.0000023678185],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046845115,0.000030600513,0.9957854,0.000039394883,0.000019686553,0.00009052254,0.00009048442,0.000040662424,0.000029992794,0.00024406517,0.00002006169,0.003140647],"study_design_scores_gemma":[0.0019870715,0.00018511208,0.9852162,0.0020883826,0.000012412116,0.00026855705,0.00001004088,0.009739727,0.00009755726,0.0000941337,0.0002211147,0.000079674704],"about_ca_topic_score_codex":0.00013269499,"about_ca_topic_score_gemma":0.00008861134,"teacher_disagreement_score":0.010569214,"about_ca_system_score_codex":0.000081752885,"about_ca_system_score_gemma":0.00007709109,"threshold_uncertainty_score":0.2900111},"labels":[],"label_agreement":null},{"id":"W3113468922","doi":"10.23889/ijpds.v5i5.1520","title":"Supported Playgroup Participation During Infancy and Developmental Health at School Entry: The Healthy Baby Community Support Program in Manitoba, Canada","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"","keywords":"Developmental psychology; Psychology; Gerontology; Medicine","score_opus":0.10003551116399052,"score_gpt":0.40338465452538663,"score_spread":0.3033491433613961,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113468922","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.963301,0.000020588457,0.000052247346,0.03497321,0.0007761113,0.0005591011,0.000083399136,0.000021427846,0.00021290073],"genre_scores_gemma":[0.9945459,0.00008919185,0.0014070809,0.003254324,0.00021831502,0.000023462826,0.00039488045,0.0000054374377,0.00006142704],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977614,0.00018016821,0.0005023946,0.00022390936,0.0009922757,0.00033983774],"domain_scores_gemma":[0.9988024,0.00010560798,0.0002904276,0.00013145761,0.00023004551,0.00044004535],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0020266538,0.00008770742,0.00010093402,0.0001034314,0.0022981337,0.00039583162,0.0010342473,0.00002409452,0.000108309316],"category_scores_gemma":[0.001542052,0.000076562006,0.0000129903365,0.0003799178,0.00014777273,0.0013646322,0.00031169038,0.0002641844,0.000004778246],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000713753,0.00007582781,0.96251607,0.000009623372,0.000012943848,0.000002664441,0.013633003,0.0000404747,0.000018900084,0.0006975415,0.006783868,0.016137706],"study_design_scores_gemma":[0.00043804434,0.000036041743,0.9691324,0.000025224994,0.0000017747686,0.0000128562315,0.0073259063,0.00030517415,0.000011354755,0.0000810789,0.022537775,0.000092324684],"about_ca_topic_score_codex":0.2627798,"about_ca_topic_score_gemma":0.8147616,"teacher_disagreement_score":0.55198175,"about_ca_system_score_codex":0.0013894861,"about_ca_system_score_gemma":0.005190733,"threshold_uncertainty_score":0.9990007},"labels":[],"label_agreement":null},{"id":"W3115008811","doi":"10.23889/ijpds.v5i5.1616","title":"Green-Blue Spaces and Mental Health: A Longitudinal Data Linkage Study","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Welsh; Cohort; Mental health; Geography; Linked data; Record linkage; Cohort study; Quarter (Canadian coin); Medicine; Demography; Longitudinal study; Environmental health; Gerontology; Population; Computer science; World Wide Web; Psychiatry","score_opus":0.15500428737052116,"score_gpt":0.4069935367241954,"score_spread":0.2519892493536743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3115008811","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9308642,0.00013593616,0.005825597,0.06003789,0.0011451415,0.0006842076,0.0012222009,0.000033927103,0.0000508636],"genre_scores_gemma":[0.9920815,0.00008768244,0.005276415,0.0015416384,0.000434054,0.0000024915278,0.00047227019,0.000009632223,0.0000942807],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974333,0.00004314332,0.0003858176,0.00069916045,0.001157,0.0002815844],"domain_scores_gemma":[0.9987265,0.000036731475,0.0003041852,0.0005019998,0.00004315797,0.00038743793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016306043,0.000119271834,0.00014360828,0.00008350788,0.0007273483,0.00042486296,0.0028483558,0.000020512207,0.00019108465],"category_scores_gemma":[0.00022935506,0.0001046967,0.000016863101,0.0002807291,0.0001959738,0.0038054383,0.002354212,0.0001765142,0.000036943024],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005438627,0.000087031825,0.97074056,0.0000042551105,0.000014772038,0.000006638959,0.0010398652,0.0000672433,0.00008300368,0.000080829486,0.015749367,0.012072051],"study_design_scores_gemma":[0.0009731845,0.00041751147,0.86862445,0.000022586752,0.000011025152,0.0001000433,0.00091385766,0.08398286,0.0000025044003,0.00012531507,0.044636976,0.00018965601],"about_ca_topic_score_codex":0.004250232,"about_ca_topic_score_gemma":0.006235761,"teacher_disagreement_score":0.10211608,"about_ca_system_score_codex":0.00017206754,"about_ca_system_score_gemma":0.00009649535,"threshold_uncertainty_score":0.6425108},"labels":[],"label_agreement":null},{"id":"W3115634801","doi":"10.23889/ijpds.v5i5.1541","title":"How Are Linkage Results Using Privacy-Preserving Record Linkage Different?","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Linkage (software); Record linkage; Computer science; Internet privacy; Genetics; Biology; Medicine; Environmental health; Gene","score_opus":0.5276143466944776,"score_gpt":0.49682370186658736,"score_spread":0.030790644827890234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3115634801","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34191114,0.00004977829,0.5510169,0.09457855,0.007851099,0.00052246393,0.0036549428,0.0000788617,0.0003362393],"genre_scores_gemma":[0.9701872,0.000040026698,0.0255436,0.001640388,0.0014291807,0.000002656388,0.0005006329,0.000013384182,0.0006429182],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9936215,0.00016141144,0.0010833092,0.0009865627,0.0037982867,0.0003488734],"domain_scores_gemma":[0.9952088,0.0006061457,0.0013844689,0.0012905066,0.0011562658,0.0003538399],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0059504155,0.00017595035,0.00025643205,0.00048411405,0.00071295275,0.0057339724,0.0113269435,0.00005355501,0.00007523073],"category_scores_gemma":[0.039546516,0.00013586857,0.000106272164,0.00082092365,0.00014513527,0.009278892,0.004301073,0.00027781763,0.000027096852],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019162024,0.00059480267,0.12710801,0.000093694354,0.00034464244,0.00024648313,0.0036563047,0.009085793,0.012784941,0.024503421,0.31158197,0.50808376],"study_design_scores_gemma":[0.0014549829,0.00009411268,0.062416945,0.0001485304,0.000030423025,0.00003401712,0.0013507252,0.560946,0.00025675297,0.020440485,0.35243136,0.00039570758],"about_ca_topic_score_codex":0.00007995835,"about_ca_topic_score_gemma":0.0000865472,"teacher_disagreement_score":0.62827605,"about_ca_system_score_codex":0.0001481602,"about_ca_system_score_gemma":0.00010074869,"threshold_uncertainty_score":0.99529815},"labels":[],"label_agreement":null},{"id":"W3117820268","doi":"10.23889/ijpds.v5i3.1352","title":"Indicators of missing Electronic Medical Record (EMR) discharge summaries: A retrospective study on data from a large Canadian cohort","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Heart Failure Treatment and Management","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Missing data; Medicine; Medical record; Logistic regression; Electronic medical record; Comorbidity; Cohort; Electronic records; Emergency medicine; Retrospective cohort study; Internal medicine; Database; Statistics","score_opus":0.06340873080193209,"score_gpt":0.39006686658174633,"score_spread":0.32665813577981423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3117820268","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9488561,0.00003807755,0.005783362,0.039774142,0.0010374576,0.0011306831,0.0031333694,0.000028400536,0.00021840946],"genre_scores_gemma":[0.9943658,0.000022984217,0.0010971155,0.0008577491,0.00038743482,0.000005401302,0.0032302232,0.00000984514,0.000023429162],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99716187,0.000036729012,0.0004194161,0.0005123381,0.0015759956,0.0002936478],"domain_scores_gemma":[0.9985024,0.0000577319,0.00021579991,0.0005428385,0.00018640711,0.0004948605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015165844,0.000108243556,0.00021890923,0.00036124457,0.00023714344,0.00012341818,0.0015067043,0.000036636146,0.0004096591],"category_scores_gemma":[0.0025643508,0.00008759133,0.000032933047,0.0003826915,0.00006911811,0.000896756,0.00039714892,0.0002459401,0.00001196298],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016216304,0.0002328548,0.9858131,0.0000028365164,0.00024974215,0.00005048578,0.00031916803,8.1759526e-7,0.000025292346,0.0010789144,0.0076432205,0.0044214292],"study_design_scores_gemma":[0.0020475993,0.0005212967,0.9249558,0.00010530832,0.00014530886,0.000014744593,0.0005178345,0.0156158,0.00001761363,0.0003259722,0.055612225,0.000120525074],"about_ca_topic_score_codex":0.015893925,"about_ca_topic_score_gemma":0.023540504,"teacher_disagreement_score":0.060857303,"about_ca_system_score_codex":0.0004560392,"about_ca_system_score_gemma":0.0011476411,"threshold_uncertainty_score":0.99427736},"labels":[],"label_agreement":null},{"id":"W3128404685","doi":"10.23889/ijpds.v6i1.1400","title":"Offering nicotine patches to all households in a community with high smoking rates: Pilot test of a population-based approach to promote tobacco cessation","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Smoking Behavior and Cessation","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Public Health Ontario; University of Waterloo; University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Canada Research Chairs; Institute of Neurosciences, Mental Health and Addiction; Public Health Agency; Public Health Agency of Canada","keywords":"Nicotine; Smoking cessation; Abstinence; Medicine; Environmental health; Population; Community health; Distribution (mathematics); Demography; Intervention (counseling); Test (biology); Public health; Psychiatry; Nursing","score_opus":0.12941298042946234,"score_gpt":0.3805260361090471,"score_spread":0.25111305567958475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128404685","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98129225,0.0000035190976,0.016739162,0.0009683393,0.00035901874,0.0004245535,0.00016341754,0.000023869832,0.00002587154],"genre_scores_gemma":[0.97985864,0.0000017367258,0.017639626,0.00038562075,0.00011561509,0.000024763967,0.0019410776,0.00001830111,0.000014650587],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977113,0.000059519913,0.0005608463,0.0003382248,0.0011199391,0.00021018255],"domain_scores_gemma":[0.9979746,0.00014358197,0.0002978131,0.0005003595,0.00093569723,0.00014798311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016507731,0.00013450974,0.00021843657,0.0004882958,0.00020837403,0.00020520021,0.0006766967,0.00004126675,0.0000113319475],"category_scores_gemma":[0.0015782121,0.000120113524,0.000030240077,0.0009059728,0.00003499355,0.00095495855,0.00017276703,0.0002600229,3.2836363e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021437989,0.000572465,0.97115093,0.000025671981,0.000016129121,0.0000035420742,0.00031978043,0.013851234,0.010619065,0.0001354237,0.000025920666,0.0030654317],"study_design_scores_gemma":[0.0013947774,0.00034396115,0.9838937,0.00047314644,0.00004001125,0.00005932331,0.00020714878,0.0068631363,0.006432682,0.0000933396,0.000063992775,0.00013480817],"about_ca_topic_score_codex":0.002663197,"about_ca_topic_score_gemma":0.00063376303,"teacher_disagreement_score":0.012742716,"about_ca_system_score_codex":0.00043951624,"about_ca_system_score_gemma":0.00027757316,"threshold_uncertainty_score":0.48980874},"labels":[],"label_agreement":null},{"id":"W3129961804","doi":"10.23889/ijpds.v6i1.1407","title":"Use of administrative record linkage to measure medical and social risk factors for early developmental vulnerability in Ontario, Canada","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Hospital for Sick Children; McMaster University; University of Toronto","funders":"","keywords":"Medical record; Population; Concordance; Vulnerability (computing); Record linkage; Residence; Medicine; Demography; Psychology; Gerontology; Environmental health; Computer security","score_opus":0.48513685475496204,"score_gpt":0.4814978207620087,"score_spread":0.0036390339929533444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129961804","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97331697,0.0000018967792,0.021128356,0.0020342388,0.0012200744,0.0002019148,0.0020707203,0.0000021217072,0.000023717894],"genre_scores_gemma":[0.9851521,0.0000021082674,0.014071227,0.0002462538,0.00005049428,0.0000050850313,0.00029113173,0.0000027042033,0.00017889723],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9957493,0.0001317442,0.0008077153,0.0004679415,0.002675541,0.00016776637],"domain_scores_gemma":[0.99701047,0.0012039985,0.00036648617,0.00021555988,0.0010469761,0.00015651381],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0062231338,0.00008309659,0.00017615962,0.00020127055,0.00031438848,0.0005349795,0.0014642831,0.0000363927,0.00016176683],"category_scores_gemma":[0.024767831,0.00006870209,0.000033542103,0.00031067154,0.000105895626,0.0020538303,0.0005824234,0.00016780898,4.950027e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019472852,0.00009999465,0.9307928,0.00000422215,0.000038705803,0.0000140612,0.0017013403,0.00007327213,0.0000674438,0.0027289053,0.0058241766,0.058460355],"study_design_scores_gemma":[0.00033998396,0.00003695442,0.9611774,0.00002353011,0.0000058737164,0.000009383715,0.0011920709,0.0011799282,0.00010906082,0.003089428,0.0327403,0.00009605643],"about_ca_topic_score_codex":0.6119447,"about_ca_topic_score_gemma":0.98665935,"teacher_disagreement_score":0.37471467,"about_ca_system_score_codex":0.00049201126,"about_ca_system_score_gemma":0.002942187,"threshold_uncertainty_score":0.98344696},"labels":[],"label_agreement":null},{"id":"W3134320576","doi":"10.23889/ijpds.v5i4.1393","title":"A commentary on the value of hospital data for covid-19 pandemic surveillance and planning","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Ottawa Public Health; Ottawa Hospital","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Public health; Medical emergency; Health care; Public hospital; Medicine; Unit (ring theory); Business; Data science; Computer science; Nursing; Psychology; Infectious disease (medical specialty); Disease; Political science","score_opus":0.12901159375738336,"score_gpt":0.4403597145464793,"score_spread":0.31134812078909596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134320576","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86964047,0.00045095276,0.039133146,0.054480117,0.003302881,0.0008190087,0.032085333,0.00003753781,0.000050567618],"genre_scores_gemma":[0.9794142,0.000083748266,0.0047966903,0.0056971638,0.00045324405,0.000006791367,0.009520341,0.000008853982,0.000018930801],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983619,0.000050649865,0.00034642257,0.00040420794,0.0006842448,0.00015259559],"domain_scores_gemma":[0.9974702,0.000745553,0.00028826206,0.00085017754,0.00048073527,0.00016504986],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0022674708,0.00008515966,0.00015230772,0.00010100076,0.0002596094,0.00012493327,0.0014045318,0.00002065333,0.0000213798],"category_scores_gemma":[0.009318244,0.00006337694,0.000032290198,0.00016206095,0.000186311,0.00077805057,0.0006688732,0.00011034921,6.3554825e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041303932,0.00014310669,0.9091144,0.000040861796,0.00011771915,0.000025392214,0.00010346906,0.00047516433,0.00052061287,0.0023594466,0.082481705,0.004205076],"study_design_scores_gemma":[0.003396281,0.00026693742,0.7137569,0.00029165536,0.00006317397,0.000364419,0.00047249632,0.13046363,0.000090353424,0.0028765958,0.14771007,0.000247474],"about_ca_topic_score_codex":0.000066032306,"about_ca_topic_score_gemma":0.000037791113,"teacher_disagreement_score":0.1953575,"about_ca_system_score_codex":0.00012399476,"about_ca_system_score_gemma":0.00037823545,"threshold_uncertainty_score":0.9990267},"labels":[],"label_agreement":null},{"id":"W3156103863","doi":"10.23889/ijpds.v6i1.1406","title":"Mapping Three Versions of the International Classification of Diseases to Categories of Chronic Conditions","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"CancerCare Manitoba; Research Institute in Oncology and Hematology; University of Manitoba","funders":"Winnipeg Foundation","keywords":"Schema crosswalk; ICD-10; Diagnosis code; Medical diagnosis; Computer science; Medicine; Data mining; Geography; Population; Pathology; Psychiatry; Environmental health","score_opus":0.37427620505811166,"score_gpt":0.5272327507167389,"score_spread":0.15295654565862726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3156103863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85875636,0.00010117646,0.09752964,0.021316865,0.015856389,0.0007996601,0.0043359064,0.00002176342,0.001282266],"genre_scores_gemma":[0.9972232,0.00003760935,0.0014241593,0.000247487,0.0003078867,0.000013010613,0.0006151442,0.0000039628626,0.00012753741],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976472,0.000058781003,0.00093486893,0.00015491058,0.001049107,0.00015511826],"domain_scores_gemma":[0.99585474,0.00035583187,0.00095909194,0.00037682574,0.0023453247,0.00010818564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011704896,0.00005886846,0.00013532094,0.0002809467,0.0005777618,0.000020247993,0.001388201,0.000044021497,0.0002258367],"category_scores_gemma":[0.0044003758,0.000045546534,0.00005586351,0.0004801342,0.00017058439,0.0008309072,0.0004396186,0.00017984262,0.0000049694795],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022831894,0.00032757616,0.67369366,0.0005000339,0.00014975491,0.0000011516986,0.0032897908,0.002464836,0.03798388,0.22765943,0.031228835,0.022472719],"study_design_scores_gemma":[0.0006149842,0.000037351114,0.93950325,0.00069488044,0.000021059797,0.0000071697673,0.0016538798,0.032108787,0.0006555734,0.0044239936,0.02020813,0.00007095206],"about_ca_topic_score_codex":0.00013730442,"about_ca_topic_score_gemma":0.00020830544,"teacher_disagreement_score":0.26580957,"about_ca_system_score_codex":0.00029089997,"about_ca_system_score_gemma":0.0017305166,"threshold_uncertainty_score":0.52679783},"labels":[],"label_agreement":null},{"id":"W3160071274","doi":"10.23889/ijpds.v6i1.1419","title":"impact of workers’ compensation benefit cessation on welfare and health service use","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare innovation and challenges","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute for Work & Health; Public Health Ontario; University of Toronto","funders":"State Insurance Regulatory Authority","keywords":"Business; Legislation; Workers' compensation; Actuarial science; Service (business); Health care; Incentive; Welfare; Social work; Emergency department; Medicine; Environmental health; Compensation (psychology); Economics; Marketing; Nursing; Psychology; Political science; Economic growth","score_opus":0.3115515450667756,"score_gpt":0.5209351283475545,"score_spread":0.20938358328077888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3160071274","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8840197,0.00004758606,0.001397551,0.112458654,0.0013792132,0.00018721833,0.00030937238,0.000019706336,0.00018103156],"genre_scores_gemma":[0.9965764,0.00019804656,0.0018686523,0.0006286708,0.00022219749,0.0000017313997,0.00044771653,0.0000050238787,0.000051516403],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981122,0.0000729282,0.00040974023,0.0002539641,0.0009680459,0.0001831249],"domain_scores_gemma":[0.9968018,0.00010842794,0.00044047227,0.00020545654,0.0022971884,0.00014668959],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020690188,0.00006965092,0.0001099381,0.00025113526,0.0008082118,0.0003811479,0.0005338895,0.000042403608,0.00007106357],"category_scores_gemma":[0.00080619875,0.000065994274,0.000029907811,0.00056937156,0.0000892961,0.0022635078,0.00009163953,0.00010903245,0.0000012913073],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008182613,0.00015083066,0.47611284,0.000020960504,0.000051138675,0.000002718751,0.0033074752,0.00080224994,0.00013920615,0.38637272,0.0009899393,0.13196807],"study_design_scores_gemma":[0.0003356647,0.00005951576,0.9837564,0.00009753459,0.0000025627,0.000011725581,0.0016228835,0.0022737805,0.000012279924,0.0021162522,0.009630278,0.0000810863],"about_ca_topic_score_codex":0.0040448387,"about_ca_topic_score_gemma":0.007841564,"teacher_disagreement_score":0.5076436,"about_ca_system_score_codex":0.00041526646,"about_ca_system_score_gemma":0.0008114139,"threshold_uncertainty_score":0.62161934},"labels":[],"label_agreement":null},{"id":"W3164594747","doi":"10.23889/ijpds.v6i1.1386","title":"Indigenizing our Research","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; University of New Brunswick; Women's College Hospital; University of Northern British Columbia; University of British Columbia; AIDS Vancouver","funders":"","keywords":"Indigenous; Participatory action research; Citizen journalism; Community-based participatory research; Public relations; Sociology; Population; Political science; Ecology","score_opus":0.24930274796365912,"score_gpt":0.5481076999183465,"score_spread":0.29880495195468737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164594747","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85748655,0.0004589031,0.006158812,0.021093426,0.041976694,0.00097252487,0.00032582105,0.00009788868,0.071429394],"genre_scores_gemma":[0.97680014,0.0019972108,0.0077813435,0.00010468381,0.0045128483,0.0000017649428,0.00029892806,0.000010181497,0.008492886],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963757,0.00023293521,0.00034107282,0.0003641867,0.002162281,0.00052382983],"domain_scores_gemma":[0.9953455,0.00015470517,0.00016995832,0.00033936038,0.003744489,0.00024603965],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009375624,0.000061422405,0.00007921524,0.0004394055,0.013428679,0.0010578918,0.0021667364,0.000058167996,0.000074906035],"category_scores_gemma":[0.0005791426,0.0000562046,0.000035581845,0.0008094604,0.00020152432,0.002951687,0.00002644103,0.00026383094,0.00003956769],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026156224,0.00018243995,0.0125596905,0.000008019463,0.000027878737,0.000024575584,0.07390508,0.00005869722,0.000135947,0.9002035,0.0035724938,0.009295488],"study_design_scores_gemma":[0.00016508061,0.0000140273805,0.007077963,0.0000350303,0.000003885462,0.00004881239,0.00922916,0.00026858645,0.0001550446,0.011848764,0.9710547,0.000098947494],"about_ca_topic_score_codex":0.020548834,"about_ca_topic_score_gemma":0.23787792,"teacher_disagreement_score":0.9674822,"about_ca_system_score_codex":0.0006598129,"about_ca_system_score_gemma":0.024633532,"threshold_uncertainty_score":0.9999791},"labels":[],"label_agreement":null},{"id":"W3164975740","doi":"10.23889/ijpds.v6i1.1412","title":"Linking National Immigration Data to Provincial Repositories: The case of Canada","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick; SickKids Foundation; University of Manitoba; University of Toronto; Manitoba Health","funders":"University of Manitoba","keywords":"Linkage (software); Immigration; Geography; Record linkage; Demography; Demographic economics; Health care; Refugee; Political science; Sociology; Economics; Population; Law","score_opus":0.0942210322749539,"score_gpt":0.43361812624300067,"score_spread":0.33939709396804674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164975740","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9094319,0.00020907854,0.036640923,0.018194962,0.026941948,0.0007191514,0.0066819317,0.00002395073,0.0011561826],"genre_scores_gemma":[0.9921207,0.0000040028694,0.0035489916,0.00070513075,0.0015493145,0.000009296766,0.0017394114,0.0000067565725,0.00031641955],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99767715,0.00007042118,0.0006129082,0.00042318896,0.0010058271,0.00021050642],"domain_scores_gemma":[0.99633133,0.00023158046,0.00039074908,0.0007282644,0.0021855058,0.00013254234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022593648,0.00008116698,0.000092860646,0.0001349259,0.00073144643,0.00023895448,0.0018661479,0.000032952543,0.00007469622],"category_scores_gemma":[0.0021049539,0.00006586871,0.000020757827,0.00042079054,0.000054936296,0.001226524,0.0003568457,0.00013988932,0.0000022121844],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009024215,0.0005986451,0.086500116,0.00007902867,0.00041749162,0.0014210427,0.014167459,0.0038985487,0.0036966149,0.37881166,0.37047985,0.1390271],"study_design_scores_gemma":[0.0030334708,0.00028033386,0.39796066,0.00030155168,0.00013608955,0.0296817,0.01396742,0.1250855,0.0014332763,0.012073912,0.4150822,0.0009638821],"about_ca_topic_score_codex":0.13400894,"about_ca_topic_score_gemma":0.71887034,"teacher_disagreement_score":0.5848614,"about_ca_system_score_codex":0.00026546713,"about_ca_system_score_gemma":0.0033615464,"threshold_uncertainty_score":0.87175775},"labels":[],"label_agreement":null},{"id":"W3170814968","doi":"10.23889/ijpds.v6i1.1410","title":"Characterizing mental health/addictions and assault visits in the year prior to death: a population-based linked cohort study of homicide victims","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Gun Ownership and Violence Research","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Public Health Ontario; Health Canada","funders":"","keywords":"Homicide; Medicine; Health care; Emergency department; Suicide prevention; Population; Poison control; Injury prevention; Occupational safety and health; Mental health; Family medicine; Medical emergency; Psychiatry; Environmental health","score_opus":0.10752952352642246,"score_gpt":0.47179115959044265,"score_spread":0.3642616360640202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170814968","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9887541,0.000020278609,0.00036778246,0.009394091,0.000606639,0.0006616054,0.00012702854,0.0000074155437,0.000061067796],"genre_scores_gemma":[0.9982137,0.000048537575,0.0009955469,0.00033584618,0.00016489282,0.000015641835,0.00019178462,0.0000043845425,0.000029627525],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99727005,0.0002444944,0.00039218747,0.0002943678,0.0015611711,0.00023771275],"domain_scores_gemma":[0.9987566,0.0001923952,0.00019730712,0.00022116848,0.00050101825,0.0001314963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004891269,0.00006522155,0.00012100176,0.0003267187,0.00087942334,0.00037998304,0.0009691394,0.000029790515,0.000023298742],"category_scores_gemma":[0.0012725649,0.000053894804,0.000024850182,0.0005466878,0.000052615476,0.001024833,0.00013816153,0.00016838477,0.0000016304713],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003301688,0.00015859668,0.985495,0.0000020572647,0.000009291373,0.0000022425536,0.0051528877,0.00010001074,0.0002829638,0.0012586438,0.0000524415,0.0074528498],"study_design_scores_gemma":[0.00040272807,0.00006384418,0.98954964,0.00006646852,0.000004264427,0.0000058549836,0.0064707384,0.0021654055,0.00001035844,0.00014063666,0.0010632029,0.000056855493],"about_ca_topic_score_codex":0.0051046466,"about_ca_topic_score_gemma":0.009232374,"teacher_disagreement_score":0.009459646,"about_ca_system_score_codex":0.0002922067,"about_ca_system_score_gemma":0.0005480152,"threshold_uncertainty_score":0.77167326},"labels":[],"label_agreement":null},{"id":"W3176469351","doi":"10.23889/ijpds.v6i1.1417","title":"SEEDS of Indigenous Population Health Data Linkage","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"First Nations Health and Social Secretariat of Manitoba; Laurentian University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Canadian Institutes of Health Research","keywords":"Linkage (software); Indigenous; Geography; Population; Genetics; Biology; Sociology; Demography; Gene; Ecology","score_opus":0.09291446882645245,"score_gpt":0.45300172283404716,"score_spread":0.3600872540075947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3176469351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9450424,0.0010476079,0.01675655,0.0076497863,0.0207799,0.0012945834,0.002677911,0.00009141635,0.004659883],"genre_scores_gemma":[0.96853024,0.0041562105,0.01580705,0.00027835078,0.0022937737,0.0000011135326,0.0073664295,0.0000157395,0.0015510917],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99646455,0.00020685267,0.00077222334,0.00048659957,0.001628911,0.00044083476],"domain_scores_gemma":[0.9963893,0.00015513982,0.00080674357,0.0008494753,0.0015404403,0.00025887444],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.006130624,0.00010066282,0.00018643652,0.00036416997,0.0055167647,0.00039172056,0.0032759325,0.00007245209,0.00008995493],"category_scores_gemma":[0.00033107825,0.000094775336,0.000041695737,0.0006661,0.00021925251,0.0038452358,0.000053501957,0.00017559412,0.00000700609],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010675709,0.0011220813,0.17798379,0.00013916122,0.00016820728,0.00002089549,0.18604107,0.00063237513,0.0001252638,0.5596936,0.0033964457,0.070570365],"study_design_scores_gemma":[0.00066335796,0.00008567411,0.19855717,0.00019682416,0.00002892148,0.000107511456,0.004059036,0.0029000354,0.000094522664,0.010544509,0.7824262,0.00033623693],"about_ca_topic_score_codex":0.07993927,"about_ca_topic_score_gemma":0.33253437,"teacher_disagreement_score":0.7790298,"about_ca_system_score_codex":0.0005592809,"about_ca_system_score_gemma":0.020277496,"threshold_uncertainty_score":0.9957779},"labels":[],"label_agreement":null},{"id":"W3177106611","doi":"10.23889/ijpds.v6i1.1362","title":"Concept Libraries for Automatic Electronic Health Record Based Phenotyping: A Review","year":2021,"lang":"en","type":"review","venue":"International Journal for Population Data Science","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Resource (disambiguation); Process (computing); Disease; Data science; Order (exchange); Grey literature; Reuse; MEDLINE; Medicine; Political science; Business; Engineering; Pathology","score_opus":0.3015893624057827,"score_gpt":0.5882200091183958,"score_spread":0.28663064671261307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177106611","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.948877e-7,0.93442684,0.043680545,0.0041652774,0.009769167,0.0060726684,0.0017357001,0.00009831575,0.00005099148],"genre_scores_gemma":[0.0000041793073,0.970111,0.011072204,0.0038026753,0.00236387,0.0009697389,0.010945466,0.00009298033,0.0006378836],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99060506,0.0013021106,0.003943582,0.0011158563,0.0014114644,0.0016219182],"domain_scores_gemma":[0.98868936,0.002728312,0.005204578,0.0012563277,0.0016516786,0.00046973178],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.01148805,0.0004786779,0.0022305462,0.0006688181,0.0022698978,0.00029229833,0.0044556777,0.00026406284,0.0003250187],"category_scores_gemma":[0.006826902,0.00040129092,0.00045710203,0.0010005671,0.00012965938,0.0019160946,0.000490663,0.0014971095,0.000037400056],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.000007886362,0.00004146321,0.000018376177,0.03318648,0.000094823954,0.0000012059828,0.00004384578,0.000001636952,4.9599237e-8,0.010590195,0.055182233,0.9008318],"study_design_scores_gemma":[0.0004498813,0.00012844034,0.000004372651,0.13261674,0.0001471138,0.000054085736,0.000028376728,0.005200304,2.5015124e-8,0.00058348145,0.8604981,0.0002890987],"about_ca_topic_score_codex":0.0002580461,"about_ca_topic_score_gemma":0.00026789677,"teacher_disagreement_score":0.9005427,"about_ca_system_score_codex":0.00436518,"about_ca_system_score_gemma":0.045505308,"threshold_uncertainty_score":0.9998439},"labels":[],"label_agreement":null},{"id":"W3196987242","doi":"","title":"Understanding variations in the trajectories of academic achievement and mental health service utilization of foreign-born adolescents in British Columbia, Canada: A population-based cohort study","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Mental health; Cohort; Population; Service (business); Cohort study; Psychology; Immigration; Demography; Mental health service; Gerontology; Medicine; Geography; Environmental health; Psychiatry; Business; Sociology; Marketing","score_opus":0.12228516453878875,"score_gpt":0.40103124340350266,"score_spread":0.2787460788647139,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196987242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9925098,0.00007545539,0.0041740076,0.0011197383,0.0006847035,0.000743815,0.0006791561,0.000002756666,0.0000105733],"genre_scores_gemma":[0.99822676,0.000022220429,0.00025115782,0.00035512328,0.000038866747,0.00001694812,0.0010780548,0.000005013055,0.000005825069],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977575,0.00018106909,0.00079318904,0.0002709438,0.0008220138,0.00017529418],"domain_scores_gemma":[0.9988641,0.00010585153,0.00047638098,0.00019195082,0.00030190987,0.00005980324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020484435,0.00005930742,0.00015075269,0.00016803948,0.00026837256,0.000106924876,0.00048803465,0.00003166841,0.000028868724],"category_scores_gemma":[0.0002448722,0.000073907184,0.0000136865065,0.0006669905,0.0000314315,0.00050246436,0.000046625064,0.00014927128,5.1867087e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025331132,0.00019938032,0.99584085,0.000022255523,0.000011820396,0.0000017822098,0.0013080804,0.0002448727,0.0000049563096,0.001618446,0.00014208048,0.0005801403],"study_design_scores_gemma":[0.0010990583,0.00004328184,0.98564976,0.00013905976,0.000006679394,0.000019495028,0.0058582113,0.0063981726,8.7342863e-7,0.0007091341,0.000022772101,0.000053478754],"about_ca_topic_score_codex":0.7815961,"about_ca_topic_score_gemma":0.99020666,"teacher_disagreement_score":0.20861053,"about_ca_system_score_codex":0.00058079866,"about_ca_system_score_gemma":0.0010301806,"threshold_uncertainty_score":0.30138475},"labels":[],"label_agreement":null},{"id":"W3200669805","doi":"10.23889/ijpds.v6i1.1650","title":"Machine learning for identification of frailty in Canadian primary care practices","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Frailty in Older Adults","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; University of Manitoba; McMaster University; Dalhousie University; Manitoba Health; University of British Columbia; University of Calgary","funders":"Canadian Frailty Network; Michael Smith Health Research BC","keywords":"Machine learning; Context (archaeology); Receiver operating characteristic; Medicine; Artificial intelligence; Medical record; Primary care; Oversampling; Computer science; Family medicine; Internal medicine","score_opus":0.09551632604470203,"score_gpt":0.4260697510684341,"score_spread":0.3305534250237321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3200669805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9509138,0.0014796756,0.019550053,0.016884984,0.00592902,0.0012768011,0.00271612,0.000032026135,0.0012175438],"genre_scores_gemma":[0.98586094,0.00006802517,0.008637867,0.00015735009,0.00017906528,0.0000074189215,0.0047117397,0.000007907283,0.0003696714],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99847955,0.000023177547,0.00045770977,0.00026792206,0.0005944411,0.00017721605],"domain_scores_gemma":[0.9973482,0.00012928997,0.0005652937,0.0002527205,0.0015711644,0.00013333782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011000212,0.00006135654,0.00011446679,0.0004042746,0.00015906568,0.00013075898,0.00055744,0.000034845805,0.00002576838],"category_scores_gemma":[0.007419151,0.00006157855,0.00003673582,0.00028155878,0.000053666412,0.0014688555,0.00008531443,0.00015501856,0.0000015298544],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022090864,0.00011234878,0.89490575,0.00018416095,0.00005608962,0.00003470623,0.0007907731,0.002959913,0.0235317,0.001844465,0.00048809726,0.07487111],"study_design_scores_gemma":[0.0016190547,0.00007503126,0.86033714,0.0002638726,0.000039732586,0.0003181343,0.00044170357,0.089559324,0.002661053,0.0004928173,0.044074707,0.00011741649],"about_ca_topic_score_codex":0.01848004,"about_ca_topic_score_gemma":0.075631134,"teacher_disagreement_score":0.08659941,"about_ca_system_score_codex":0.0005740341,"about_ca_system_score_gemma":0.0013931574,"threshold_uncertainty_score":0.988056},"labels":[],"label_agreement":null},{"id":"W3202418933","doi":"10.23889/ijpds.v6i1.1653","title":"Factors Affecting Access to Administrative Health Data for Research in Canada: A Study Protocol","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"","keywords":"Receipt; Stakeholder; Protocol (science); Inclusion (mineral); Data collection; Health data; Business; Medicine; Public relations; Psychology; Political science; Health care; Accounting; Alternative medicine; Sociology","score_opus":0.8544295047813003,"score_gpt":0.7599307233599555,"score_spread":0.09449878142134482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3202418933","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7596382,0.000008605151,0.004683504,0.091919586,0.010457248,0.12855317,0.0044957744,0.000022617587,0.00022131426],"genre_scores_gemma":[0.9773135,0.0000027528085,0.0022626473,0.0025785337,0.0015566297,0.014317453,0.0017799321,0.00001920814,0.00016932686],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99569774,0.00056770415,0.0009690211,0.00062657753,0.0013544093,0.0007845746],"domain_scores_gemma":[0.9945829,0.0015768677,0.00046973536,0.00084280764,0.002084153,0.0004435591],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.013543016,0.00010145177,0.00019927585,0.00047606512,0.0020890918,0.0003350349,0.0036170683,0.000032043376,0.00005253825],"category_scores_gemma":[0.010853561,0.00008634619,0.000013359509,0.0010671137,0.000030815758,0.0027847674,0.0017095767,0.0005054673,0.0000017822762],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00018581678,0.000385587,0.8392473,0.00016797379,0.00002460816,0.000004764052,0.00720036,0.00017990448,0.000018952149,0.0011182274,0.13582604,0.015640479],"study_design_scores_gemma":[0.0009976134,0.00015797438,0.852033,0.00026490146,0.0000019304161,0.0000045623487,0.04257565,0.0054568006,0.000005674259,0.0003984052,0.09798987,0.00011359489],"about_ca_topic_score_codex":0.7093573,"about_ca_topic_score_gemma":0.94745004,"teacher_disagreement_score":0.23809269,"about_ca_system_score_codex":0.003961893,"about_ca_system_score_gemma":0.04626256,"threshold_uncertainty_score":0.9998617},"labels":[],"label_agreement":null},{"id":"W3204448007","doi":"10.23889/ijpds.v6i1.1686","title":"Multigenerational Health Research using Population-Based Linked Databases: An International Review","year":2021,"lang":"en","type":"review","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"Canadian Institutes of Health Research; European Commission","keywords":"Population; Geography; Database; Population health; Construct (python library); Health care; Environmental health; Medicine; Economic growth; Computer science","score_opus":0.7325304048142112,"score_gpt":0.6767003649026033,"score_spread":0.05583003991160784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204448007","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002909741,0.96697885,0.0053662304,0.0068761455,0.01396787,0.0018277487,0.0047943583,0.000056003744,0.00010370988],"genre_scores_gemma":[0.00006649356,0.9369887,0.025156721,0.00259327,0.0046716253,0.00005740285,0.030232117,0.00004540079,0.00018824353],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.98870915,0.001659614,0.0021570753,0.0012077133,0.005271599,0.0009948298],"domain_scores_gemma":[0.9913747,0.0012305832,0.0015877371,0.0011264898,0.0038446488,0.00083584135],"candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.022388529,0.0003496945,0.0010710626,0.0012827147,0.0040743565,0.0018565042,0.0059560747,0.00017376697,0.0005859522],"category_scores_gemma":[0.013753755,0.0003311163,0.00032430724,0.0013758966,0.00035398535,0.00574166,0.0006530739,0.0008855978,0.000014366794],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012390944,0.00026075888,0.002647046,0.0035766945,0.00012593078,0.000019891633,0.00016391255,0.0003099189,1.5583471e-7,0.053252615,0.009686811,0.92994386],"study_design_scores_gemma":[0.00020309174,0.000016456195,0.0007147593,0.022786489,0.0000604432,0.000039018196,0.00012136874,0.005298247,2.9186202e-8,0.00012046,0.9703271,0.00031253425],"about_ca_topic_score_codex":0.017571058,"about_ca_topic_score_gemma":0.005306363,"teacher_disagreement_score":0.9606403,"about_ca_system_score_codex":0.0035929654,"about_ca_system_score_gemma":0.016201828,"threshold_uncertainty_score":0.9999141},"labels":[],"label_agreement":null},{"id":"W3205416661","doi":"10.23889/ijpds.v6i1.1672","title":"Chronic Disease Surveillance in Alberta’s Tomorrow Project using Administrative Health Data","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Alberta","funders":"University of Alberta; Alberta Cancer Foundation; Government of Alberta; Partenariat Canadien Contre Le Cancer; Alberta Health Services","keywords":"Medicine; Cohort; Incidence (geometry); Disease; Population; Cohort study; Depression (economics); Prospective cohort study; Demography; Environmental health; Internal medicine","score_opus":0.3208371015703519,"score_gpt":0.5280984484199787,"score_spread":0.20726134684962677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3205416661","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76006466,0.0061244373,0.047248483,0.14425446,0.017491618,0.0056342203,0.015439025,0.00018154916,0.003561554],"genre_scores_gemma":[0.9872836,0.0001787857,0.0040974645,0.00035634317,0.0006906349,0.000005367632,0.0070431703,0.000012127144,0.0003324962],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99758,0.00005561564,0.0004896667,0.00063262205,0.00094223715,0.00029986262],"domain_scores_gemma":[0.9981168,0.00008279514,0.00029340247,0.0009386858,0.00036421712,0.00020412561],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011747514,0.00011888821,0.00017926884,0.00027976735,0.00019955165,0.00038205844,0.0013964159,0.000016692338,0.00008293344],"category_scores_gemma":[0.0016914472,0.00011319562,0.000035426652,0.00048738724,0.0001228064,0.0025206183,0.00076202425,0.00013958267,0.0000031368909],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017571177,0.0017873672,0.82556915,0.0007744267,0.0005991909,0.0018287767,0.0006214128,0.00874164,0.0011361225,0.041684434,0.031135125,0.084365234],"study_design_scores_gemma":[0.002764897,0.000118251766,0.53733265,0.0006823328,0.000052482526,0.00037450556,0.00036832382,0.4306526,0.000021126245,0.0010525658,0.02629787,0.0002823876],"about_ca_topic_score_codex":0.001580318,"about_ca_topic_score_gemma":0.0062590656,"teacher_disagreement_score":0.42191094,"about_ca_system_score_codex":0.0009702399,"about_ca_system_score_gemma":0.007748768,"threshold_uncertainty_score":0.99787635},"labels":[],"label_agreement":null},{"id":"W3207035469","doi":"10.23889/ijpds.v6i1.1397","title":"Describing agreement in the Main Condition coding field using Canadian ICD-11 inpatient data","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Health Sciences Centre; University of Calgary","funders":"","keywords":"Comparability; Medicine; Inpatient care; Emergency department; Coding (social sciences); Medical emergency; Family medicine; Health care; Statistics; Nursing","score_opus":0.647462925510609,"score_gpt":0.5624528094982154,"score_spread":0.08501011601239361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3207035469","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7770817,0.00007697585,0.14851388,0.053042777,0.01573861,0.0012874138,0.0023901525,0.000025494002,0.001842972],"genre_scores_gemma":[0.98368776,0.000038449893,0.004562066,0.008319639,0.0005464306,0.0000080999125,0.0027979917,0.0000041361104,0.00003544433],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974938,0.00019336949,0.00073676254,0.00025058043,0.00094355043,0.00038190922],"domain_scores_gemma":[0.99797344,0.00044178983,0.00035025744,0.00053504034,0.00047364325,0.000225821],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0066836933,0.00007092359,0.0000920215,0.00032553455,0.0016820696,0.0001764675,0.0017129721,0.00005987404,0.00027863038],"category_scores_gemma":[0.0058510583,0.00005652828,0.000014987086,0.0003383675,0.00003796893,0.0022149114,0.0003751156,0.0004121,0.000011100393],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014481854,0.00018319259,0.66521174,0.00023168325,0.00005072926,0.00014825808,0.014229109,0.0034990266,0.000853852,0.09310458,0.11720929,0.10513372],"study_design_scores_gemma":[0.0016299952,0.000056913726,0.10971178,0.0016922224,0.000027313023,0.00017446883,0.00991464,0.76803094,0.000047018028,0.0025677648,0.10586568,0.00028127676],"about_ca_topic_score_codex":0.028278764,"about_ca_topic_score_gemma":0.12137332,"teacher_disagreement_score":0.7645319,"about_ca_system_score_codex":0.0007983905,"about_ca_system_score_gemma":0.0023938222,"threshold_uncertainty_score":0.9996176},"labels":[],"label_agreement":null},{"id":"W3210772458","doi":"10.23889/ijpds.v6i3.1683","title":"Supporting policy and practice in Ontario through ICES’ Applied Health Research Question (AHRQ) Program","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; Public Health Ontario; Health Sciences Centre; Sunnybrook Hospital; University of Toronto; Sunnybrook Health Science Centre; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Christian ministry; Government (linguistics); Health care; Reputation; Quality (philosophy); Process (computing); Public relations; Business; Nursing; Political science; Knowledge management; Medicine; Computer science","score_opus":0.4377950595728576,"score_gpt":0.6843070801380333,"score_spread":0.24651202056517574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210772458","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2892675,0.0014488328,0.014104568,0.6041198,0.01738565,0.007132513,0.00055036746,0.0002665693,0.06572418],"genre_scores_gemma":[0.78509134,0.0012368477,0.16599698,0.039299965,0.0025302398,0.0002054089,0.002142383,0.000038710237,0.003458096],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9960183,0.0005318027,0.00095277134,0.00047448158,0.0012984698,0.0007241658],"domain_scores_gemma":[0.9954332,0.0016757238,0.0006554477,0.0003535579,0.001669106,0.0002129292],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.015435492,0.000093532435,0.0001874402,0.0004521488,0.0016472809,0.00023475492,0.0007956016,0.00007476439,0.00007803647],"category_scores_gemma":[0.012763932,0.00008817038,0.000019966994,0.0006623999,0.000119862416,0.003303871,0.00070591085,0.001026443,0.000011227022],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000604398,0.00049315457,0.33804435,0.0002055635,0.000045368994,0.00006902998,0.016082453,0.00008336035,0.0003428999,0.2752239,0.02904362,0.3397619],"study_design_scores_gemma":[0.0010613676,0.00009283058,0.37228677,0.00020662807,0.0000049385867,0.00015343176,0.0031003866,0.000516114,0.0000066397633,0.017603854,0.60483927,0.00012778622],"about_ca_topic_score_codex":0.089532115,"about_ca_topic_score_gemma":0.18876709,"teacher_disagreement_score":0.57579565,"about_ca_system_score_codex":0.0034637875,"about_ca_system_score_gemma":0.016142352,"threshold_uncertainty_score":0.99965245},"labels":[],"label_agreement":null},{"id":"W3217141020","doi":"10.23889/ijpds.v6i1.1680","title":"Data Harmonization and Data Pooling from Cohort Studies: A Practical Approach for Data Management","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"York University; Alberta Health Services; University of Calgary","funders":"","keywords":"Pooling; Harmonization; Matching (statistics); Computer science; Variable (mathematics); Construct (python library); Data mining; Sample (material); Econometrics; Data science; Statistics; Artificial intelligence; Mathematics","score_opus":0.36385083373474125,"score_gpt":0.5330212202993609,"score_spread":0.1691703865646197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3217141020","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0045222943,0.0010018726,0.95969874,0.012221822,0.0011890192,0.0011804042,0.019997412,0.000023111772,0.0001653313],"genre_scores_gemma":[0.05101548,0.0023766742,0.67829,0.0006975921,0.00067952916,0.00002316496,0.26644504,0.00001819642,0.0004543406],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996514,0.000041292784,0.00046642276,0.001217782,0.00149104,0.00026943366],"domain_scores_gemma":[0.99551255,0.00033280125,0.00022851789,0.002585595,0.0011458116,0.0001947205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033310875,0.0001191866,0.00018509052,0.00021614309,0.00036633262,0.0006358256,0.003332434,0.000027693988,0.000026705955],"category_scores_gemma":[0.007890948,0.00010694859,0.000014869371,0.00026998227,0.00013181363,0.0051927427,0.007965586,0.00014441303,0.0000031553818],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014336357,0.0019266609,0.11513926,0.00092610024,0.007945925,0.00036132117,0.00022309116,0.0012741165,0.0015878552,0.037068058,0.5032619,0.32885206],"study_design_scores_gemma":[0.0013508158,0.000030392477,0.041927252,0.000109055654,0.00035784306,0.00009203387,0.00055266457,0.85013825,0.00001766472,0.0018150808,0.10348066,0.0001282811],"about_ca_topic_score_codex":0.000041278276,"about_ca_topic_score_gemma":0.000040550945,"teacher_disagreement_score":0.84886414,"about_ca_system_score_codex":0.00013013165,"about_ca_system_score_gemma":0.00032590516,"threshold_uncertainty_score":0.99285334},"labels":[],"label_agreement":null},{"id":"W4200606750","doi":"10.23889/ijpds.v6i1.1678","title":"Characterizing social and policy determinants of hospital length of stay among paediatric inpatients with diabetes using linked population-based data","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Hyperglycemia and glycemic control in critically ill and hospitalized patients","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick","funders":"Diabetes Canada; Economic and Social Research Council; Fondation de la recherche en santé du Nouveau-Brunswick","keywords":"Diabetes mellitus; Medicine; Population; Intensive care medicine; Pediatrics; Environmental health; Endocrinology","score_opus":0.05525625197393555,"score_gpt":0.3766956070753088,"score_spread":0.3214393551013732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200606750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973145,0.000033152697,0.00050358626,0.00032181625,0.0005468947,0.00018059123,0.0010865346,0.0000055963214,0.000007324687],"genre_scores_gemma":[0.99311775,0.000013760265,0.0049326997,0.00008624343,0.00032804714,0.0000018730746,0.0015041269,0.00001061084,0.0000048987886],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99804384,0.00002663263,0.0005746637,0.00033795444,0.0008142402,0.00020268427],"domain_scores_gemma":[0.9979097,0.000103307626,0.00048493806,0.00033880267,0.0010486449,0.00011459061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004224679,0.00011031164,0.00027484447,0.00031510665,0.00020161648,0.00008322029,0.00055759033,0.000052621886,0.000009652903],"category_scores_gemma":[0.0013956261,0.00009262726,0.000039313272,0.0003261875,0.00017879477,0.0013217635,0.000300448,0.0001105261,9.917162e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014617853,0.00015187029,0.99047923,0.000041221032,0.000045734167,0.0000063572875,0.00010201519,0.000016158965,0.0017529414,0.00007046224,0.000004341185,0.0071834913],"study_design_scores_gemma":[0.0020218159,0.00023416246,0.92742306,0.00021394956,0.00011084084,0.000011602953,0.000065821216,0.06928908,0.00039817428,0.00009182816,0.000033462235,0.00010621391],"about_ca_topic_score_codex":0.00024670424,"about_ca_topic_score_gemma":0.000033522396,"teacher_disagreement_score":0.06927292,"about_ca_system_score_codex":0.00007937996,"about_ca_system_score_gemma":0.00044650925,"threshold_uncertainty_score":0.377723},"labels":[],"label_agreement":null},{"id":"W4206039573","doi":"10.23889/ijpds.v5i4.1682","title":"Pivoting data and analytic capacity to support Ontario’s COVID-19 response","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Health Sciences Centre; Vector Institute; Trillium Health Centre; University of Toronto; University Health Network; Public Health Ontario; Hospital for Sick Children; Sunnybrook Health Science Centre; McMaster University; Women's College Hospital","funders":"Agency for Healthcare Research and Quality","keywords":"Public health; Pandemic; Population; Health care; Analytics; Population health; Public relations; Business; Political science; Environmental health; Coronavirus disease 2019 (COVID-19); Medicine; Nursing; Data science; Computer science; Disease; Infectious disease (medical specialty)","score_opus":0.6458393543368621,"score_gpt":0.5551504100211131,"score_spread":0.09068894431574903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206039573","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8987742,0.0000119622455,0.07503817,0.021663727,0.0014502308,0.00041068127,0.0025548886,0.000047470614,0.000048651495],"genre_scores_gemma":[0.9624501,0.0000032832377,0.032934204,0.003911045,0.00014939935,0.000014443572,0.0002490505,0.000008358749,0.0002801067],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99701667,0.00019972035,0.00061819714,0.00068809517,0.001188069,0.000289223],"domain_scores_gemma":[0.9954477,0.0027327687,0.00041768656,0.00083008665,0.00023752135,0.00033421762],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.015788883,0.00012228516,0.00021107224,0.00033735688,0.0014851324,0.00025553093,0.0037643113,0.000020305613,0.0003350099],"category_scores_gemma":[0.06925625,0.00010789775,0.000034116154,0.00034813822,0.00014660196,0.0012497498,0.0054867,0.00027557142,0.0000033610324],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002240949,0.00033632436,0.79287225,0.000045809054,0.0002271803,0.000108317734,0.004676656,0.0075011393,0.0010194703,0.044327132,0.13886939,0.007775351],"study_design_scores_gemma":[0.0012816335,0.00047203718,0.30577055,0.000029610375,0.00008611905,0.0007402432,0.00076413853,0.07551602,0.0000083943105,0.1462155,0.468598,0.0005177455],"about_ca_topic_score_codex":0.005917625,"about_ca_topic_score_gemma":0.010715059,"teacher_disagreement_score":0.48710173,"about_ca_system_score_codex":0.0016135622,"about_ca_system_score_gemma":0.00062236463,"threshold_uncertainty_score":0.9998148},"labels":[],"label_agreement":null},{"id":"W4206902948","doi":"10.23889/ijpds.v7i1.1701","title":"Closing the loop: From system-based data to evidence-influenced policy and practice","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Work (physics); Evidence-based policy; Government (linguistics); Public relations; Population; Research policy; Data sharing; Political science; Public administration; Sociology; Engineering; Medicine","score_opus":0.26770704671989326,"score_gpt":0.5371566112385167,"score_spread":0.2694495645186234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206902948","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25721455,0.0008883129,0.021296619,0.6982001,0.0142005365,0.0015777624,0.0054725995,0.00010559332,0.0010439056],"genre_scores_gemma":[0.9798827,0.000060020673,0.0068757846,0.011462489,0.0014193363,0.000014517809,0.00018949938,0.000006392021,0.00008921542],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967414,0.00035013238,0.00036593617,0.00038855092,0.0018499893,0.0003040026],"domain_scores_gemma":[0.99588317,0.0025112098,0.000324903,0.0006156812,0.00043983504,0.0002251756],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0095912665,0.000070297574,0.000091467016,0.000208422,0.0040183924,0.0011922431,0.00464367,0.000017975502,0.000047739264],"category_scores_gemma":[0.025551608,0.000056891826,0.00001873134,0.0005322697,0.00019156646,0.0044215876,0.001368193,0.00017547453,0.0000037939622],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015302859,0.00025927444,0.16939984,0.00008436456,0.00017195294,0.000070662434,0.017257653,0.020452611,0.0006635577,0.57497925,0.059287906,0.15584263],"study_design_scores_gemma":[0.0005204775,0.000059669663,0.106760755,0.000277844,0.000047212558,0.00007744853,0.019405212,0.065635,0.0000061470123,0.001428054,0.8055152,0.00026697994],"about_ca_topic_score_codex":0.05206061,"about_ca_topic_score_gemma":0.002030084,"teacher_disagreement_score":0.7462273,"about_ca_system_score_codex":0.0007457155,"about_ca_system_score_gemma":0.0017574639,"threshold_uncertainty_score":0.9998446},"labels":[],"label_agreement":null},{"id":"W4210391004","doi":"10.23889/ijpds.v6i1.1395","title":"Development of a prognostic prediction model to estimate the risk of multiple chronic diseases","year":2021,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Western University","funders":"","keywords":"Univariate; Copula (linguistics); Covariate; Logistic regression; Medicine; Multivariate statistics; Predictive modelling; Cohort; Retrospective cohort study; Statistics; Econometrics; Internal medicine; Mathematics","score_opus":0.08491830340952311,"score_gpt":0.42287445012175906,"score_spread":0.33795614671223595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210391004","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8583922,0.000121772595,0.138743,0.00069698977,0.00066757627,0.00043106292,0.0008587279,0.0000148775525,0.000073791605],"genre_scores_gemma":[0.96726763,0.000022825694,0.031991675,0.000025017938,0.00010538726,0.000013185652,0.0005154736,0.000005087119,0.000053692278],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99842554,0.000012375757,0.0004046136,0.00020349567,0.00083772384,0.00011625501],"domain_scores_gemma":[0.99859977,0.00006923509,0.00026496226,0.0003033442,0.00067636336,0.00008630503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004965785,0.00006320816,0.00009845811,0.00014408164,0.00016718492,0.00007031196,0.0005548142,0.000010584384,0.00002176286],"category_scores_gemma":[0.0019272845,0.000045746194,0.00004149204,0.00023096068,0.00008528832,0.0005680609,0.0003087923,0.00005486423,0.0000012322341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047349863,0.00070263824,0.5112814,0.00026002238,0.00049652136,0.000014059832,0.00064887264,0.39328182,0.013319405,0.0069763823,0.0019286117,0.07061681],"study_design_scores_gemma":[0.0005547344,0.000030983636,0.41179255,0.00018407783,0.00010587298,0.000015320064,0.00008331916,0.585361,0.00066164794,0.0005442178,0.00062842784,0.000037823174],"about_ca_topic_score_codex":0.000013115818,"about_ca_topic_score_gemma":0.00006727197,"teacher_disagreement_score":0.19207922,"about_ca_system_score_codex":0.00020729391,"about_ca_system_score_gemma":0.0011898746,"threshold_uncertainty_score":0.23072788},"labels":[],"label_agreement":null},{"id":"W4212784128","doi":"10.23889/ijpds.v5i4.1697","title":"Validating the QCOVID risk prediction algorithm for risk of mortality from COVID-19 in the adult population in Wales, UK.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Immune responses and vaccinations","field":"Immunology and Microbiology","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIHR Leicester Biomedical Research Centre; Engineering and Physical Sciences Research Council; Welsh Ambulance Services NHS Trust; Health and Social Care Research and Development Division; Public Health Agency; Queen's University Belfast; Wales Institute of Social and Economic Research and Data; University of Oxford; Queen's University; Economic and Social Research Council; Swansea University; University of Leicester; Medical Research Council; Department of Health and Social Care; Queen Mary University of London; National Institute for Health and Care Research; Scottish Government; Chief Scientist Office, Scottish Government Health and Social Care Directorate; Public Health Wales; Wellcome Trust; University College London; British Heart Foundation; Llywodraeth Cymru; Cardiff University; London School of Hygiene and Tropical Medicine; UK Research and Innovation; Health and Care Research Wales; Imperial College London","keywords":"Medicine; Population; Brier score; Retrospective cohort study; Demography; Cohort; Coronavirus disease 2019 (COVID-19); Cohort study; Pandemic; Risk assessment; Algorithm; Computer science; Machine learning; Disease; Environmental health; Internal medicine","score_opus":0.061501085440158317,"score_gpt":0.38619173062436746,"score_spread":0.32469064518420915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212784128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9344309,0.00021995796,0.048950575,0.0011174021,0.0021576222,0.00064681296,0.012460364,0.000009849507,0.0000065302406],"genre_scores_gemma":[0.99308985,0.0000817874,0.0014259631,0.00018012109,0.00009057464,0.000080997874,0.00501683,0.0000057636225,0.000028111177],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979116,0.0006039048,0.0006958443,0.00029357406,0.0003046958,0.0001904372],"domain_scores_gemma":[0.9973629,0.0011833317,0.00080394413,0.0003929243,0.00023964199,0.00001726074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059591765,0.000091670685,0.00012710843,0.00032294335,0.0012763074,0.00008971231,0.0016962477,0.000044818902,0.00009159847],"category_scores_gemma":[0.004444296,0.00006501889,0.000074477066,0.0004019009,0.000085654494,0.0006346149,0.00027095355,0.00038409134,8.846612e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003217563,0.00017969518,0.9318564,0.0000036847125,0.00009812157,0.0000013129597,0.0014077869,0.018036406,0.0012020315,0.0031047903,0.0012492689,0.042538747],"study_design_scores_gemma":[0.001640894,0.000080802034,0.90616584,0.0000129568225,0.000049016682,0.00004589047,0.0016885258,0.07732421,0.00008236316,0.008590882,0.0042355624,0.000083073115],"about_ca_topic_score_codex":0.018005757,"about_ca_topic_score_gemma":0.0021318567,"teacher_disagreement_score":0.059287805,"about_ca_system_score_codex":0.00039367343,"about_ca_system_score_gemma":0.00021662246,"threshold_uncertainty_score":0.98853344},"labels":[],"label_agreement":null},{"id":"W4214652336","doi":"10.23889/ijpds.v7i2.1739","title":"Sociodemographic, living environment and maternal health associations with stillbirth in a tertiary healthcare setting in Kano, Northern Nigeria","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Infection and Immunity","funders":"","keywords":"Medicine; Obstetrics; Pregnancy; Health facility; Obstructed labour; Observational study; Referral; Socioeconomic status; Pediatrics; Population; Environmental health; Family medicine; Caesarean section; Health services","score_opus":0.02127404427011096,"score_gpt":0.33313111266084017,"score_spread":0.3118570683907292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214652336","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.980935,0.00015286909,0.00026722546,0.017371176,0.00032344426,0.00033492097,0.0005965207,0.000011054242,0.000007822702],"genre_scores_gemma":[0.9956497,0.00012559284,0.001896682,0.0019436929,0.00010759234,0.000016545026,0.00023144008,0.000010015112,0.00001875073],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977961,0.000089912966,0.00050537044,0.0003401963,0.00094472925,0.00032369883],"domain_scores_gemma":[0.99917644,0.000056036384,0.00035722274,0.00016060546,0.00008190973,0.00016778894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00194642,0.00009982743,0.00016854214,0.00042247967,0.0005192479,0.00009791426,0.00043469225,0.000019361269,0.000028108183],"category_scores_gemma":[0.000092409,0.000088035,0.00002260005,0.00021482499,0.000057806217,0.00058279576,0.00032183787,0.00033136096,7.364206e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006917078,0.00007805933,0.9942758,0.000017525337,0.0000108959475,0.000017824426,0.00059669756,0.00067663455,0.00003737846,0.00017891139,0.000030066196,0.004011022],"study_design_scores_gemma":[0.0007277252,0.0001511547,0.99294883,0.00018142078,0.0000033757506,0.00037223907,0.00044712384,0.0042643934,0.0000012246776,0.00047129134,0.0003516449,0.00007957895],"about_ca_topic_score_codex":0.0026594861,"about_ca_topic_score_gemma":0.0030228458,"teacher_disagreement_score":0.015427482,"about_ca_system_score_codex":0.0010191775,"about_ca_system_score_gemma":0.00038363782,"threshold_uncertainty_score":0.40203652},"labels":[],"label_agreement":null},{"id":"W4214693600","doi":"10.23889/ijpds.v7i2.1736","title":"Improving the diagnosis of cancer in primary care: a feasibility economic analysis of the ThinkCancer! study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Intervention (counseling); Medicine; Welsh; Attendance; Health care; Government (linguistics); Cancer; Activity-based costing; Family medicine; Nursing; Medical emergency; Business; Political science; Geography","score_opus":0.12731335036786157,"score_gpt":0.4803032419438475,"score_spread":0.3529898915759859,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214693600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9939877,0.0002031209,0.0000519154,0.0031535262,0.0009942357,0.0005229835,0.0010743468,0.0000022825154,0.0000098884775],"genre_scores_gemma":[0.9993253,0.000040458617,0.000069429196,0.00038912822,0.000075717595,0.000031633,0.00005677333,0.0000032374164,0.00000837641],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983095,0.00006970009,0.00048309148,0.00022025457,0.0008047353,0.00011269768],"domain_scores_gemma":[0.9984992,0.00018968707,0.00051733543,0.00047300037,0.00027740304,0.000043377415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020239828,0.000053791868,0.00017802278,0.00036501567,0.00027769234,0.000033048032,0.0012325455,0.000010499237,0.00008677155],"category_scores_gemma":[0.0005653583,0.000033875498,0.000090372574,0.0007020604,0.000093551644,0.00038119394,0.0005396623,0.00017975598,5.8666267e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013937482,0.0000822901,0.97011095,0.000015513499,0.00008946102,6.258821e-7,0.0009541907,0.015388671,0.00013541248,0.000056522276,0.000028540528,0.012998449],"study_design_scores_gemma":[0.00054590247,0.00008066701,0.9781411,0.000023314984,0.00017774876,0.000003461963,0.00077942107,0.019969877,0.00004338749,0.000054946424,0.00014933174,0.000030790252],"about_ca_topic_score_codex":0.02439687,"about_ca_topic_score_gemma":0.013933298,"teacher_disagreement_score":0.012967658,"about_ca_system_score_codex":0.0020897544,"about_ca_system_score_gemma":0.0016357822,"threshold_uncertainty_score":0.9820998},"labels":[],"label_agreement":null},{"id":"W4214900227","doi":"10.23889/ijpds.v7i1.1689","title":"Describing the linkage between administrative social assistance and health care databases in Ontario, Canada","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ministry of Children, Community and Social Services; Hospital for Sick Children; Public Health Ontario; Trillium Health Centre; SickKids Foundation; University of Toronto; Institute for Clinical Evaluative Sciences; Centre for Addiction and Mental Health","funders":"","keywords":"Record linkage; Database; Linkage (software); Representativeness heuristic; Population; Service (business); Medicine; Christian ministry; Business; Computer science; Environmental health; Psychology; Political science","score_opus":0.658627486546011,"score_gpt":0.5247302681115205,"score_spread":0.13389721843449054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214900227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8447929,0.00033616202,0.031094844,0.09269216,0.0075874454,0.0011377933,0.021552417,0.00002092005,0.0007853394],"genre_scores_gemma":[0.99583536,0.000003464738,0.0014218373,0.001397553,0.00012730592,0.000008851744,0.0010553836,0.0000028925233,0.00014734776],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9958652,0.00018323533,0.00062713993,0.0004379714,0.002676481,0.00020994511],"domain_scores_gemma":[0.99836254,0.0004102063,0.0005003981,0.00037086176,0.00025846632,0.000097518976],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008498362,0.00007593482,0.00012977161,0.00020596058,0.0019301508,0.00073768094,0.003242055,0.0000056522676,0.00012437247],"category_scores_gemma":[0.0013674576,0.000057768426,0.000020201998,0.00040371675,0.00012139684,0.0019720653,0.0015376693,0.00027629588,4.5029188e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010101724,0.00006185213,0.6898725,0.000005317736,0.000040462903,0.00003270306,0.007442559,0.0008270035,0.000008927401,0.053502362,0.10063249,0.14747283],"study_design_scores_gemma":[0.0002691165,0.000026787453,0.7507484,0.00001249254,0.0000039711917,0.0000142125255,0.010889794,0.0006294482,0.000002185257,0.0015077624,0.23580638,0.00008947956],"about_ca_topic_score_codex":0.7720856,"about_ca_topic_score_gemma":0.9880192,"teacher_disagreement_score":0.21593359,"about_ca_system_score_codex":0.0013878202,"about_ca_system_score_gemma":0.0028588434,"threshold_uncertainty_score":0.9993692},"labels":[],"label_agreement":null},{"id":"W4220853000","doi":"10.23889/ijpds.v5i4.1716","title":"Quantifying Depression-Related Language on Social Media During the COVID-19 Pandemic","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Mental Health via Writing","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; Western University","funders":"Western Canada Research Grid; Compute Canada; Canadian Institute for Advanced Research","keywords":"Pandemic; Mental health; Coronavirus disease 2019 (COVID-19); Depression (economics); Social media; Population; Psychology; Demography; Incidence (geometry); Geography; Medicine; Computer science; Sociology; Psychiatry; World Wide Web; Mathematics","score_opus":0.31148328122078794,"score_gpt":0.5349691278455393,"score_spread":0.22348584662475135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220853000","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98926115,0.000097356555,0.00029234332,0.0025665043,0.006730264,0.00021300615,0.0005592324,0.000045648267,0.00023452191],"genre_scores_gemma":[0.9972452,0.000004460551,0.00016671322,0.0014931372,0.000545219,0.000030827927,0.0003546108,0.000011733466,0.00014812194],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975515,0.00018765079,0.00044466354,0.00035782764,0.0011763936,0.00028196682],"domain_scores_gemma":[0.99851525,0.00056735374,0.00042197312,0.0002860031,0.00007534689,0.00013410451],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0033930345,0.000083388426,0.000083782725,0.0002746272,0.0030387982,0.00014973641,0.0021335585,0.000027855851,0.0011976984],"category_scores_gemma":[0.0013045835,0.00006726048,0.000041326373,0.00030216094,0.0001022255,0.00051528297,0.0005931265,0.00044898337,0.000020784864],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014103611,0.00037142978,0.80945,0.000035323414,0.00013335925,0.00023261124,0.03239181,0.00516372,0.007349947,0.037363466,0.017230734,0.088867284],"study_design_scores_gemma":[0.003455249,0.00005799891,0.94282943,0.00004215526,0.000023060351,0.0032814343,0.017065022,0.009196091,0.00003646011,0.0019033593,0.02176095,0.00034880906],"about_ca_topic_score_codex":0.00026062276,"about_ca_topic_score_gemma":0.000094150106,"teacher_disagreement_score":0.13337946,"about_ca_system_score_codex":0.000707638,"about_ca_system_score_gemma":0.00013818702,"threshold_uncertainty_score":0.9997153},"labels":[],"label_agreement":null},{"id":"W4224223202","doi":"10.23889/ijpds.v5i4.1710","title":"Estimating surge in COVID-19 cases, hospital resources and PPE demand with the interactive and locally-informed COVID-19 Health System Capacity Planning Tool","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"Public Health Agency; Public Health Agency of Canada","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Surge Capacity; Personal protective equipment; Pandemic; Medicine; Virology; Medical emergency; Infectious disease (medical specialty); Disease; Pathology","score_opus":0.26493751084519196,"score_gpt":0.48253653981973776,"score_spread":0.2175990289745458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224223202","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8754029,0.00017593543,0.10332625,0.01953537,0.00043370744,0.00063317904,0.0004396519,0.000042065312,0.0000109114],"genre_scores_gemma":[0.9864449,0.000014101249,0.011012002,0.0023187806,0.000096916774,0.000046780213,0.000051136223,0.000007751458,0.000007654278],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975315,0.00025702795,0.0006332652,0.00043594165,0.00084265653,0.00029964393],"domain_scores_gemma":[0.9917553,0.00674959,0.0008642544,0.00023515701,0.00014120978,0.00025450427],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.007484381,0.00015219089,0.00027933024,0.00024008089,0.0020449427,0.00035398762,0.0008671312,0.000022985849,0.000011794895],"category_scores_gemma":[0.028529478,0.000100955505,0.000026361498,0.00028587572,0.00033652488,0.0011788904,0.0010118996,0.00034486523,2.019706e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001198387,0.00016794635,0.85424,0.00057403155,0.00017913038,0.00025510293,0.02154454,0.08235644,0.000011957483,0.023053726,0.0115464525,0.0048723104],"study_design_scores_gemma":[0.004138229,0.0010640634,0.18046966,0.00076673215,0.000060948045,0.0047676186,0.031730007,0.7277954,0.000002142812,0.022295196,0.026134517,0.0007754886],"about_ca_topic_score_codex":0.0024721117,"about_ca_topic_score_gemma":0.0010403866,"teacher_disagreement_score":0.6737703,"about_ca_system_score_codex":0.0018223163,"about_ca_system_score_gemma":0.0005563704,"threshold_uncertainty_score":0.9992543},"labels":[],"label_agreement":null},{"id":"W4225158835","doi":"10.23889/ijpds.v7i1.1700","title":"A more accurate approach to define abortion cohorts using linked administrative data: an application to Ontario, Canada","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Reproductive Health and Contraception","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal; McMaster University; Women's College Hospital; Hamilton Health Sciences; University of Toronto; Institute for Clinical Evaluative Sciences; University of British Columbia","funders":"Department of Family and Community Medicine, University of Toronto; Canadian Institutes of Health Research; Ministry of Health, British Columbia; Provincial Health Services Authority; Ontario Ministry of Health and Long-Term Care; University of Toronto; Michael Smith Health Research BC; Public Health Agency; Hypertension Canada; Public Health Agency of Canada","keywords":"Abortion; Medicine; Incidence (geometry); Pregnancy; Obstetrics; Confidence interval; Population; Cohort; Cohort study; Demography; Gynecology; Environmental health; Internal medicine","score_opus":0.18532952548655218,"score_gpt":0.45630427914615374,"score_spread":0.27097475365960155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225158835","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8592834,0.0000125933175,0.13228175,0.00444344,0.0014502144,0.0013704587,0.0010810639,0.000016701835,0.0000603871],"genre_scores_gemma":[0.9670749,0.0000016517445,0.023361074,0.001515255,0.0006705009,0.00007731811,0.007189561,0.0000106654825,0.00009909044],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970493,0.00004015144,0.00048473256,0.00077999657,0.00140296,0.00024291627],"domain_scores_gemma":[0.99760675,0.000021175521,0.00031487047,0.0008643672,0.0008157653,0.0003770929],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016893554,0.00011013842,0.00015523931,0.00026170045,0.0007316887,0.00015142933,0.00123661,0.000019604651,0.000036196747],"category_scores_gemma":[0.0005470447,0.00010842667,0.000016917997,0.0004809688,0.000031920128,0.0017293838,0.00041620387,0.00023482266,0.0000010121114],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009172689,0.002481522,0.44430727,0.00008729712,0.0003297225,0.00008452676,0.0053017,0.28437757,0.057100784,0.007296224,0.029004738,0.16045597],"study_design_scores_gemma":[0.0006911009,0.00028378153,0.7022182,0.000022761293,0.000048825885,0.00063614413,0.00068990025,0.24894314,0.000055366883,0.00013945074,0.04607083,0.00020050851],"about_ca_topic_score_codex":0.4069275,"about_ca_topic_score_gemma":0.3416703,"teacher_disagreement_score":0.25791094,"about_ca_system_score_codex":0.0020006897,"about_ca_system_score_gemma":0.003418806,"threshold_uncertainty_score":0.6703425},"labels":[],"label_agreement":null},{"id":"W4232215170","doi":"10.23889/ijpds.v3i4.664","title":"Preterm birth, unplanned hospital contact and mortality in infants born to teenage mothers in five countries: a cross-country comparison using linked administrative data","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child and Adolescent Health","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Pediatrics; Demography; Obstetrics","score_opus":0.18233229557051672,"score_gpt":0.5498218103733226,"score_spread":0.36748951480280584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232215170","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99109757,0.00002515191,0.0011083083,0.0005785843,0.002251757,0.00088221923,0.0039956877,0.000012914482,0.0000478177],"genre_scores_gemma":[0.996535,0.00003066658,0.0014197561,0.00078464363,0.00062391296,0.0000025008462,0.0005738339,0.000010262195,0.000019413945],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99734175,0.00010515564,0.0009050332,0.0005628626,0.00066782883,0.00041736828],"domain_scores_gemma":[0.9981038,0.00023208027,0.0005402838,0.00051029725,0.00041570727,0.0001978481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00264242,0.00013757772,0.00023500781,0.00034763577,0.00065551884,0.0002438107,0.0013377327,0.00007111935,0.000033540655],"category_scores_gemma":[0.0014479483,0.00012280594,0.000012553968,0.00033415257,0.00021520049,0.0027799793,0.0006496225,0.00040611872,0.000005457349],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033097586,0.00006477495,0.9952865,0.000023930193,0.00001046655,0.00000825545,0.0031969012,0.000055636,0.000070254224,0.0003809489,0.00025715426,0.00031417445],"study_design_scores_gemma":[0.0013303708,0.00011238975,0.93143374,0.0007033139,0.0000047780054,0.00000919651,0.001352341,0.063104756,0.0000055399037,0.00020097614,0.0016062554,0.00013632413],"about_ca_topic_score_codex":0.002485562,"about_ca_topic_score_gemma":0.008372319,"teacher_disagreement_score":0.06385277,"about_ca_system_score_codex":0.00044299083,"about_ca_system_score_gemma":0.00083467737,"threshold_uncertainty_score":0.5041787},"labels":[],"label_agreement":null},{"id":"W4234367736","doi":"10.23889/ijpds.v3i4.829","title":"Can Linked Electronic Medical Record and Administrative Data Help Us Identify Those Living With Frailty?","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; University of Manitoba; University of British Columbia; Manitoba Health","funders":"","keywords":"Medicine; Medical record; Electronic medical record; Population; Vulnerability (computing); Medical diagnosis; Gerontology; Primary care; Health care; Medical emergency; Family medicine; Environmental health; Internal medicine; Computer security","score_opus":0.20082634639797758,"score_gpt":0.5331611133300562,"score_spread":0.33233476693207864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234367736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.970157,0.00009132834,0.012785659,0.009033587,0.0064646127,0.00041598876,0.0006642346,0.000042781416,0.00034478115],"genre_scores_gemma":[0.9936017,0.00013520733,0.002781699,0.00038007656,0.0021706582,0.0000068123773,0.0005701081,0.0000114356835,0.00034234347],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973942,0.00011259907,0.0004643619,0.00048990425,0.0011339528,0.00040495064],"domain_scores_gemma":[0.99747753,0.00047045856,0.00040959462,0.0005709091,0.0008308883,0.00024061589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030050043,0.000108796514,0.00014054863,0.00022175274,0.001252902,0.00020678414,0.00220508,0.00008062551,0.00030989447],"category_scores_gemma":[0.0033204178,0.00008416652,0.000015007173,0.00027627609,0.00029476633,0.0018227071,0.0007758575,0.0004492936,0.000011085602],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059743505,0.00019764526,0.7894322,0.000049578262,0.000221304,0.00002819899,0.0051817386,0.000003395252,0.000524649,0.008340144,0.05412559,0.14129812],"study_design_scores_gemma":[0.0012412829,0.0005823915,0.9176464,0.00097532454,0.00006670475,0.0002938218,0.0028843924,0.01468672,0.00001295378,0.0035674807,0.057722867,0.00031964743],"about_ca_topic_score_codex":0.0011653077,"about_ca_topic_score_gemma":0.015253608,"teacher_disagreement_score":0.14097847,"about_ca_system_score_codex":0.00023679719,"about_ca_system_score_gemma":0.0019194027,"threshold_uncertainty_score":0.96364355},"labels":[],"label_agreement":null},{"id":"W4234804330","doi":"10.23889/ijpds.v5i4.1389","title":"Developing a Data Integrated COVID-19 Tracking System for Decision-Making and Public Use","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Dashboard; Computer science; Government (linguistics); Data science; Benchmarking; World Wide Web; Business; Marketing","score_opus":0.3197080733320304,"score_gpt":0.47189515171622576,"score_spread":0.15218707838419537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234804330","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08034226,0.000090951486,0.9018159,0.007933073,0.0012244558,0.0005750311,0.007913348,0.000098142205,0.000006874471],"genre_scores_gemma":[0.8566136,0.000023751372,0.13655467,0.0019404275,0.0003709994,0.000006985251,0.0044705574,0.000015604171,0.0000034158118],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99745715,0.00003484287,0.000602713,0.0007064553,0.0009342884,0.00026455958],"domain_scores_gemma":[0.9965021,0.00082139386,0.00040955623,0.0006476948,0.0011002024,0.00051902933],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0018379906,0.0001353083,0.00022067639,0.00032121167,0.00047841598,0.0012238871,0.0022018831,0.00003788879,0.000016110254],"category_scores_gemma":[0.04699555,0.00011654502,0.000036431655,0.00046900118,0.00011718816,0.005604439,0.00096158823,0.0001412971,0.0000029507446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030272966,0.00014467642,0.5066554,0.0005496721,0.00043293048,0.00023391018,0.00047563622,0.00080985966,0.0016512707,0.028455764,0.026795786,0.43076783],"study_design_scores_gemma":[0.0024567712,0.0000881619,0.073590815,0.00108463,0.00008428036,0.0011051169,0.00073482725,0.7597853,0.000018454011,0.00073747593,0.15996245,0.0003517113],"about_ca_topic_score_codex":0.00005206611,"about_ca_topic_score_gemma":0.00008857566,"teacher_disagreement_score":0.77627134,"about_ca_system_score_codex":0.0004885831,"about_ca_system_score_gemma":0.0013130077,"threshold_uncertainty_score":0.99981296},"labels":[],"label_agreement":null},{"id":"W4237117124","doi":"10.23889/ijpds.v4i2.1131","title":"Population Data Centre Profile: The Manitoba Centre for Health Policy","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Government (linguistics); Corporate governance; Population; Population health; Data governance; Political science; Public relations; Public administration; Sociology; Management; Engineering; Operations management; Data quality; Economics","score_opus":0.18086097539636073,"score_gpt":0.4909925594696052,"score_spread":0.3101315840732445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237117124","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011616285,0.00011226379,0.009305434,0.9671681,0.0049571134,0.0014026883,0.0051289825,0.00006510832,0.00024401024],"genre_scores_gemma":[0.94524574,0.00031053956,0.010536158,0.029480012,0.008568131,0.000009768119,0.0053117513,0.000023840606,0.00051408383],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99704784,0.00012280101,0.00055822625,0.00046000883,0.001262681,0.0005484285],"domain_scores_gemma":[0.9978525,0.0002715507,0.00048846833,0.0004810612,0.0005017115,0.00040470547],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0030841306,0.000108744534,0.00015187441,0.00012512416,0.0024134798,0.00085833285,0.0042509534,0.000042683376,0.00006612065],"category_scores_gemma":[0.0057095583,0.00008420727,0.000049679315,0.0004311882,0.00015112912,0.0031206063,0.0005232838,0.00015103318,0.0000102927725],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017645277,0.00008823147,0.2096426,0.00009285192,0.00005213558,0.000002208426,0.005491357,0.0002931398,0.0000067150645,0.39704815,0.24596557,0.1411406],"study_design_scores_gemma":[0.0005648909,0.000025731564,0.15434806,0.00007287494,0.000012448326,0.0000052635637,0.00431796,0.04470638,0.000001862619,0.0036643199,0.79210824,0.00017199207],"about_ca_topic_score_codex":0.02663656,"about_ca_topic_score_gemma":0.023741188,"teacher_disagreement_score":0.9376881,"about_ca_system_score_codex":0.000496449,"about_ca_system_score_gemma":0.0013237367,"threshold_uncertainty_score":0.9988852},"labels":[],"label_agreement":null},{"id":"W4241632110","doi":"10.23889/ijpds.v4i2.1133","title":"Population Data BC: Supporting population data science in British Columbia","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"The Quebec Population Health Research Network; University of British Columbia","funders":"","keywords":"Computer science; Data access; Linkage (software); Variety (cybernetics); Data quality; Identifier; Data science; Data management; Linked data; Record linkage; Population; Database; World Wide Web; Service (business); Business","score_opus":0.4131892460550775,"score_gpt":0.5216265395244426,"score_spread":0.10843729346936509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241632110","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8865519,0.000059636164,0.07598428,0.012562612,0.009467637,0.0012822434,0.013604172,0.0001284257,0.00035910864],"genre_scores_gemma":[0.96462756,0.00004099073,0.01679803,0.0010562412,0.0007358834,0.0000047791646,0.01654906,0.000017573191,0.00016990687],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9874048,0.00019683733,0.0023742411,0.0025281806,0.0068186345,0.00067730335],"domain_scores_gemma":[0.9926067,0.00047402378,0.0016762879,0.0036342263,0.0011583152,0.00045042348],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.027868325,0.00018510043,0.00037867462,0.00071954814,0.0013694743,0.012668324,0.028264605,0.00007032599,0.00042489826],"category_scores_gemma":[0.04174124,0.00023355822,0.000050937906,0.0030168635,0.0003963596,0.04263052,0.011638212,0.00035372857,0.000060076487],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047279314,0.0001217217,0.7225228,0.000012098623,0.00001622124,0.000035400695,0.00014836839,0.0016016827,0.0001611422,0.0019422541,0.033598654,0.23979239],"study_design_scores_gemma":[0.00048272713,0.000029140227,0.6200442,0.00005824766,0.000014402856,0.00004048931,0.0003823851,0.3510511,0.0000020421237,0.0063117584,0.021352189,0.00023136432],"about_ca_topic_score_codex":0.05802133,"about_ca_topic_score_gemma":0.1004933,"teacher_disagreement_score":0.3494494,"about_ca_system_score_codex":0.00035526612,"about_ca_system_score_gemma":0.0004666633,"threshold_uncertainty_score":0.9999306},"labels":[],"label_agreement":null},{"id":"W4246709522","doi":"10.23889/ijpds.v5i5.1424","title":"Participation in Boys &amp; Girls Clubs Of Winnipeg is Associated With Health, Social and Education Outcomes Among Metis Children","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Metis; Socioeconomic status; Population; Psychology; Attendance; Gerontology; Demography; Medicine; Developmental psychology; Sociology; Political science","score_opus":0.2983004569699677,"score_gpt":0.5498340536405917,"score_spread":0.25153359667062397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246709522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9775923,0.00003253439,0.0009204819,0.019266471,0.0006268105,0.0006925702,0.0007910753,0.000019171423,0.000058570004],"genre_scores_gemma":[0.99398607,0.000026508358,0.0017803895,0.002747448,0.00021694756,0.0000278229,0.001130237,0.000010213175,0.000074373944],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975159,0.00018295932,0.000900462,0.0003266369,0.0007664977,0.00030750074],"domain_scores_gemma":[0.9977261,0.00017130641,0.0010371011,0.00016288117,0.0006948416,0.00020777143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016054678,0.000110812805,0.00025919976,0.0003148621,0.0010141936,0.00006004659,0.0006120812,0.000082998355,0.00007746811],"category_scores_gemma":[0.0016759234,0.00010001443,0.000030427967,0.00046885276,0.00015299486,0.0017147211,0.00018834003,0.00034546465,0.000004609295],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000633191,0.00008983358,0.9868867,0.00002384498,0.000027813147,1.2980612e-7,0.0053002215,0.000047110843,0.000010280218,0.00238442,0.0027743138,0.00239206],"study_design_scores_gemma":[0.0008749594,0.00006436177,0.9949192,0.00012044625,0.00001469583,0.0000010609294,0.00047540304,0.0021629408,0.0000031310517,0.00067691307,0.0005921101,0.000094767594],"about_ca_topic_score_codex":0.0023181858,"about_ca_topic_score_gemma":0.0042181853,"teacher_disagreement_score":0.016519023,"about_ca_system_score_codex":0.0002790385,"about_ca_system_score_gemma":0.00086814247,"threshold_uncertainty_score":0.780046},"labels":[],"label_agreement":null},{"id":"W4281718863","doi":"10.23889/ijpds.v7i1.1735","title":"A Longitudinal Cohort Study of Participation in the Boys &amp; Girls Clubs of Winnipeg","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Youth Development and Social Support","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Numeracy; Longitudinal study; Neighbourhood (mathematics); Medicine; Population; Psychology; Demography; Gerontology; Environmental health; Literacy","score_opus":0.1604870825718529,"score_gpt":0.47091584908127104,"score_spread":0.31042876650941814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281718863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970365,0.0000061706132,0.00029580036,0.00062174303,0.0010208515,0.00045885606,0.000074363,0.0000041818844,0.0004815349],"genre_scores_gemma":[0.9992314,0.00000659829,0.0002883958,0.00004204181,0.00011965832,0.000031642874,0.00011795597,0.0000027232568,0.00015958388],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966508,0.00021388389,0.0005138738,0.00019158848,0.0022618086,0.00016803117],"domain_scores_gemma":[0.9987776,0.00012638938,0.0004431803,0.00019649764,0.000416764,0.000039568597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008504877,0.000050727598,0.000111079535,0.00025166216,0.00086333865,0.00010032208,0.0019922534,0.0000150149845,0.00015879903],"category_scores_gemma":[0.0010645784,0.00004349829,0.000031196443,0.0006529371,0.00016441477,0.0010372925,0.00024600816,0.00012322803,8.1952953e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000332781,0.0002544609,0.98184013,8.21252e-7,0.000013600249,0.000001147867,0.011859934,0.00025168393,0.000034010947,0.0045791827,0.00027021824,0.0008614999],"study_design_scores_gemma":[0.00029679044,0.000051944553,0.9905763,0.000003875479,0.000011427837,0.0000020884715,0.0052644904,0.00020146054,0.0000042280235,0.00087320217,0.0026624743,0.000051696272],"about_ca_topic_score_codex":0.0042008096,"about_ca_topic_score_gemma":0.0059479126,"teacher_disagreement_score":0.00873616,"about_ca_system_score_codex":0.00019434433,"about_ca_system_score_gemma":0.00036611804,"threshold_uncertainty_score":0.664019},"labels":[],"label_agreement":null},{"id":"W4293093303","doi":"10.23889/ijpds.v7i3.2060","title":"Planning for community well-being: Prioritizing and identifying local neighbourhood attributes of belonging.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Public Health","funders":"","keywords":"Neighbourhood (mathematics); Respondent; Census; Geography; Leverage (statistics); American Community Survey; Community health; Population; Metropolitan area; Public health; Environmental health; Political science; Medicine; Statistics","score_opus":0.21235228852098825,"score_gpt":0.5366904997123637,"score_spread":0.32433821119137546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293093303","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.873205,0.00011415457,0.109184764,0.008337713,0.007478545,0.0006822522,0.0006652185,0.000027576316,0.00030474793],"genre_scores_gemma":[0.9940534,0.000016111295,0.0039280867,0.00072757853,0.00052182894,0.000047187514,0.0006060643,0.00000979867,0.00008989206],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980097,0.00020172317,0.0006533018,0.0001822616,0.0005938727,0.00035914057],"domain_scores_gemma":[0.9974047,0.0009597536,0.00061240274,0.00025545937,0.0006286246,0.00013909358],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0068636253,0.00007418436,0.0001385606,0.000373821,0.0054482627,0.00009022045,0.0011973197,0.000032165954,0.000051743093],"category_scores_gemma":[0.0016819106,0.00007602532,0.000029585124,0.00026225107,0.00009937363,0.0013729807,0.00087243563,0.00052737363,6.707073e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040957582,0.0003410576,0.7056224,0.00060203305,0.00011662731,0.0000025645156,0.037285976,0.0043914593,0.0019196431,0.16170046,0.024519011,0.06308921],"study_design_scores_gemma":[0.002417936,0.0002706143,0.64355075,0.00048423564,0.000039960567,0.00011885638,0.04972331,0.14733621,0.00005005897,0.03387954,0.12180984,0.00031867143],"about_ca_topic_score_codex":0.0018517115,"about_ca_topic_score_gemma":0.00006158543,"teacher_disagreement_score":0.14294475,"about_ca_system_score_codex":0.0004388745,"about_ca_system_score_gemma":0.0006066583,"threshold_uncertainty_score":0.9958465},"labels":[],"label_agreement":null},{"id":"W4293093335","doi":"10.23889/ijpds.v7i3.2096","title":"ICES Data and Analytic Services: Eight Years Young.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Education, Law, and Society","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Analytics; Operationalization; Biobank; Service (business); Data science; Computer science; Business; Marketing","score_opus":0.09035256957814176,"score_gpt":0.44336624744786673,"score_spread":0.353013677869725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293093335","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9723604,0.00035046512,0.0014470655,0.009038095,0.011863421,0.00035718788,0.0026801957,0.000047505004,0.0018556763],"genre_scores_gemma":[0.9935261,0.00026858214,0.0025306589,0.00046103212,0.0009587656,0.0000055048013,0.0013906363,0.000006584279,0.0008521212],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975808,0.00009033291,0.0002659144,0.0004065074,0.0014381228,0.00021829829],"domain_scores_gemma":[0.9986935,0.000114006376,0.00025676927,0.0004851945,0.0003091604,0.00014132378],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004530345,0.00006390063,0.00007917226,0.00016726904,0.0023509113,0.0008281241,0.004385852,0.000021685371,0.00029922457],"category_scores_gemma":[0.00039053406,0.000067140674,0.000024368497,0.00043003954,0.00028136902,0.003996011,0.0010474547,0.00011275554,0.000001873224],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004220688,0.00021889793,0.823991,0.000015729394,0.00011947489,0.000008873869,0.0386424,0.000387429,0.00011000871,0.08492441,0.03131612,0.020223435],"study_design_scores_gemma":[0.00038767644,0.00002855062,0.17221813,0.00001998624,0.000040404764,0.000052134885,0.029014155,0.033179246,0.0000011558369,0.008380803,0.75645524,0.00022252307],"about_ca_topic_score_codex":0.0027769094,"about_ca_topic_score_gemma":0.0042268033,"teacher_disagreement_score":0.72513914,"about_ca_system_score_codex":0.00023161573,"about_ca_system_score_gemma":0.00046571475,"threshold_uncertainty_score":0.9989479},"labels":[],"label_agreement":null},{"id":"W4293093341","doi":"10.23889/ijpds.v7i3.2085","title":"The benefits and challenges of applied, partnered data-intensive research.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of British Columbia","funders":"","keywords":"General partnership; Timeline; Constructive; Public relations; Value (mathematics); Political science; Engineering ethics; Knowledge management; Management science; Process management; Business; Computer science; Engineering; Process (computing)","score_opus":0.922148362312764,"score_gpt":0.735643548639732,"score_spread":0.18650481367303196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293093341","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49414328,0.0025996936,0.0015131835,0.4547805,0.019220402,0.005241389,0.01826032,0.00008524704,0.004156002],"genre_scores_gemma":[0.99381924,0.0016987609,0.0014302268,0.002135133,0.00046855127,0.00010095988,0.00024517407,0.000010128777,0.00009181913],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9955183,0.0004125977,0.00080042536,0.00045001702,0.002322758,0.0004958923],"domain_scores_gemma":[0.99246496,0.003483835,0.0006682051,0.0009169538,0.0022876593,0.00017839801],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.025599038,0.00006773814,0.00011366724,0.0003506848,0.005926325,0.00009567735,0.0047061574,0.000020654254,0.000074888],"category_scores_gemma":[0.009593303,0.000051268205,0.000011655598,0.00045282682,0.0004415703,0.0012645359,0.0043129567,0.0004992346,0.0000068701333],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042871648,0.000042088133,0.010784671,0.000051412924,0.000044583394,0.0000024417,0.009812284,0.0004362568,0.0004696515,0.6796637,0.06664394,0.2316202],"study_design_scores_gemma":[0.0010737877,0.00010644837,0.06715713,0.000051971714,0.0000076564165,0.000040641313,0.033366363,0.015289092,0.000016870677,0.013477144,0.86928856,0.00012432916],"about_ca_topic_score_codex":0.0002643709,"about_ca_topic_score_gemma":0.0004609814,"teacher_disagreement_score":0.8026446,"about_ca_system_score_codex":0.0002470891,"about_ca_system_score_gemma":0.0010269247,"threshold_uncertainty_score":0.9987493},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"commentary","about_ca_system":false,"about_ca_topic":false,"confidence":"low"}],"label_agreement":"split"},{"id":"W4293093345","doi":"10.23889/ijpds.v7i3.2082","title":"Associations between neighbourhood fast-food environments and hypertension in Canadian adults.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; University of Toronto; Centre for Advancing Health Outcomes; McGill University Health Centre; University of Waterloo; Statistics Canada; McGill University","funders":"","keywords":"Neighbourhood (mathematics); Blood pressure; Medicine; Odds; Demography; Environmental health; Odds ratio; Logistic regression; Internal medicine; Mathematics","score_opus":0.054491159191128354,"score_gpt":0.32734130843850406,"score_spread":0.2728501492473757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293093345","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98713976,0.0001299121,0.00008933762,0.0077612773,0.0006787665,0.0002304783,0.0038244566,0.000004891728,0.00014112238],"genre_scores_gemma":[0.9968596,0.000057749254,0.0007607951,0.0004162932,0.00021993363,0.000008216111,0.0016305023,0.0000055005435,0.000041397117],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985561,0.000015987833,0.00026218753,0.00023415255,0.0007222272,0.00020935251],"domain_scores_gemma":[0.99941736,0.000051450006,0.00011759406,0.00012073516,0.00009597034,0.00019687106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006757176,0.000061009534,0.00011167793,0.00034163223,0.000675363,0.000066418186,0.0003608544,0.000017157707,0.00006290769],"category_scores_gemma":[0.00037787954,0.000060210397,0.000023973067,0.0001844342,0.000045760728,0.0005138318,0.0002729451,0.00015592792,0.0000016242109],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045671175,0.00007295853,0.9901729,0.0000015232292,0.000031698193,0.000012474619,0.00004968085,0.000076781624,0.00008350216,0.001182047,0.00091398833,0.0073567554],"study_design_scores_gemma":[0.0011375697,0.0001342716,0.9781487,0.000018771674,0.000014647236,0.000092747716,0.00014995028,0.0031134584,0.0000042392585,0.0008716087,0.016249826,0.00006423503],"about_ca_topic_score_codex":0.033298537,"about_ca_topic_score_gemma":0.021439891,"teacher_disagreement_score":0.015335838,"about_ca_system_score_codex":0.00069348514,"about_ca_system_score_gemma":0.00017560848,"threshold_uncertainty_score":0.9964163},"labels":[],"label_agreement":null},{"id":"W4293093351","doi":"10.23889/ijpds.v7i3.2075","title":"Statistical methods for assessing the impact of the Covid-19 pandemic on health services use: Paediatric primary care and mental health access.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Poisson regression; Pandemic; Medicine; Demography; Mental health; Coronavirus disease 2019 (COVID-19); Rate ratio; Population; Primary care; Health care; Gee; Generalized estimating equation; Environmental health; Family medicine; Statistics; Disease; Psychiatry","score_opus":0.28370022662609107,"score_gpt":0.6222247899173696,"score_spread":0.33852456329127856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293093351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70658904,0.0027805194,0.1406293,0.123489425,0.004569445,0.00430921,0.017567044,0.000049299364,0.000016708247],"genre_scores_gemma":[0.9716339,0.00030790383,0.0116693815,0.014795282,0.00021385455,0.000015704989,0.0013459662,0.000010768011,0.0000072349962],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978168,0.00028393054,0.0004824787,0.00028319756,0.00088127056,0.00025233717],"domain_scores_gemma":[0.9972914,0.0011636143,0.00066904456,0.00030163856,0.0002585386,0.0003157905],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004266204,0.000096950665,0.00019578794,0.0002486034,0.0016950786,0.0002996643,0.0009808632,0.000017581777,0.000018150413],"category_scores_gemma":[0.0013144067,0.000056427853,0.00006865647,0.00033766747,0.000113007685,0.00095187733,0.0005483906,0.00026290535,5.6346305e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041707954,0.00007827156,0.8032017,0.0003833808,0.00004020642,7.492178e-7,0.0015580824,0.0015017446,0.000093951625,0.000668271,0.003863418,0.18819314],"study_design_scores_gemma":[0.0011639491,0.00057321275,0.9673703,0.00008376723,0.000015065856,0.00031071302,0.0006055776,0.015641395,0.0000014481651,0.0010400133,0.01312904,0.0000655349],"about_ca_topic_score_codex":0.004204321,"about_ca_topic_score_gemma":0.0001927352,"teacher_disagreement_score":0.26504487,"about_ca_system_score_codex":0.0027799406,"about_ca_system_score_gemma":0.0053402656,"threshold_uncertainty_score":0.9996046},"labels":[],"label_agreement":null},{"id":"W4293093362","doi":"10.23889/ijpds.v7i3.2074","title":"From society to cell: Exploring the biological impacts of social exposures through linked biological and population-level child development data.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Biobank; Population; Cohort; Psychology; Medicine; Environmental health; Biology; Bioinformatics","score_opus":0.2535170291555358,"score_gpt":0.38566936670739826,"score_spread":0.13215233755186245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293093362","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98799026,0.000022714525,0.007899408,0.002014864,0.00062160334,0.00030342504,0.001093835,0.000009626638,0.000044249584],"genre_scores_gemma":[0.97693455,0.000048368907,0.020834535,0.00070282025,0.00023893247,0.000025142166,0.0012003151,0.000007453136,0.000007871353],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99736375,0.00011832498,0.00051576475,0.0006634987,0.001053906,0.00028478407],"domain_scores_gemma":[0.998934,0.00020884392,0.0003393,0.00037553368,0.0000317665,0.00011056503],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002584769,0.00012701943,0.00013628024,0.000050389943,0.0017637473,0.0001267266,0.00231785,0.000030418074,0.00037319897],"category_scores_gemma":[0.0004998097,0.00009348492,0.00003583656,0.00025033165,0.00024221759,0.0016066983,0.0038105221,0.00026086086,0.000008124111],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016971033,0.0002999554,0.89887977,0.0000054179486,0.000070439,0.000005114251,0.0100064445,0.0034808707,0.013117369,0.00035769315,0.0020375527,0.071569644],"study_design_scores_gemma":[0.00029797686,0.00004806967,0.98230463,0.000010299341,0.0000060004886,0.000015017811,0.0010353373,0.0020620322,0.00022170499,0.0006562823,0.013209021,0.00013362824],"about_ca_topic_score_codex":0.00077423884,"about_ca_topic_score_gemma":0.000072467905,"teacher_disagreement_score":0.08342484,"about_ca_system_score_codex":0.00036914085,"about_ca_system_score_gemma":0.000051287385,"threshold_uncertainty_score":0.9995358},"labels":[],"label_agreement":null},{"id":"W4293093366","doi":"10.23889/ijpds.v7i3.2095","title":"A large linked data platform to inform the COVID-19 response in British Columbia: The BC COVID-19 Cohort.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Provincial Health Services Authority; BC Centre for Disease Control","funders":"","keywords":"Pandemic; Public health; Medicine; Coronavirus disease 2019 (COVID-19); Public health surveillance; Population; Health care; Psychological intervention; Epidemiology; Family medicine; Medical emergency; Environmental health; Nursing; Political science","score_opus":0.10922815609529045,"score_gpt":0.4249872716149249,"score_spread":0.3157591155196344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293093366","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8602484,0.0001163202,0.009277781,0.074948534,0.0028615273,0.002439024,0.049933054,0.000090839436,0.00008455665],"genre_scores_gemma":[0.9564396,0.000039615003,0.00072163093,0.030617123,0.0003019151,0.00010714011,0.011040202,0.00001832579,0.00071445765],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99546105,0.00017799155,0.00076102186,0.0006558045,0.0025156974,0.0004284121],"domain_scores_gemma":[0.9958496,0.0009181672,0.0004200253,0.0018322205,0.00035665242,0.00062334153],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.015559522,0.00011601669,0.00021017191,0.00029630293,0.002203899,0.0012105881,0.0067089563,0.000032797605,0.0009317682],"category_scores_gemma":[0.030033112,0.000112154754,0.000058141628,0.0012176703,0.00024250803,0.0021391776,0.004196397,0.0005065301,0.000017577673],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026103638,0.00023331333,0.67691976,0.000018618894,0.0000927244,0.00030913742,0.0006361339,0.0035180927,0.000060032777,0.0005054362,0.31111217,0.0039842096],"study_design_scores_gemma":[0.0014373165,0.00007815621,0.42247814,0.000016291411,0.000019045072,0.001149996,0.0005983836,0.020071693,1.5871184e-7,0.00046476416,0.55357975,0.000106326],"about_ca_topic_score_codex":0.011026622,"about_ca_topic_score_gemma":0.06443271,"teacher_disagreement_score":0.25444162,"about_ca_system_score_codex":0.0016319976,"about_ca_system_score_gemma":0.003225027,"threshold_uncertainty_score":0.9999815},"labels":[],"label_agreement":null},{"id":"W4293093406","doi":"10.23889/ijpds.v7i3.2025","title":"COVID-19 testing, infection rates, and related outcomes in adults with intellectual and developmental disabilities (IDD): An application of linked administrative health data to support Ontario’s COVID-19 response.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Medicine; Population; Coronavirus disease 2019 (COVID-19); Christian ministry; Health care; Cohort; Demography; Pediatrics; Family medicine; Environmental health; Disease; Infectious disease (medical specialty)","score_opus":0.22063635443280502,"score_gpt":0.47407324097737563,"score_spread":0.25343688654457064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293093406","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.989642,0.000011964532,0.003207751,0.0049738823,0.00016570713,0.0010220319,0.00090840156,0.00002479767,0.000043428357],"genre_scores_gemma":[0.99125713,0.000009822831,0.004163543,0.0008120526,0.00001821337,0.000045303837,0.0035579116,0.000007988984,0.00012801729],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99788,0.0001076882,0.0005726941,0.00054751534,0.0007256618,0.00016645869],"domain_scores_gemma":[0.9980934,0.00063281954,0.00032547856,0.00034967673,0.00015264508,0.00044594007],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0027888205,0.00011888112,0.00019263824,0.00049951876,0.0004137235,0.00011980942,0.00054821395,0.00001814681,0.00018157886],"category_scores_gemma":[0.011187722,0.00010756978,0.00001074645,0.00041948978,0.00026455012,0.0012989708,0.0006932047,0.00017360409,6.2832595e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004675234,0.0002966832,0.97809684,0.00009830361,0.00005368719,0.000011826106,0.009794808,0.0011542257,0.00007079878,0.0008269696,0.0009829445,0.003937696],"study_design_scores_gemma":[0.003247135,0.0019583153,0.9609993,0.000070234535,0.000026484553,0.00060016534,0.010410987,0.014594917,0.000002971561,0.0006493347,0.007270453,0.00016969914],"about_ca_topic_score_codex":0.017536212,"about_ca_topic_score_gemma":0.039082095,"teacher_disagreement_score":0.021545885,"about_ca_system_score_codex":0.0021824052,"about_ca_system_score_gemma":0.0059004184,"threshold_uncertainty_score":0.9997352},"labels":[],"label_agreement":null},{"id":"W4293242898","doi":"10.23889/ijpds.v7i3.2105","title":"Public Engagement and other Essential Requirements for Data Trusts, Data Repositories and Other Data Collaborations.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick; University of British Columbia; University of Toronto","funders":"","keywords":"Stakeholder engagement; Data governance; Documentation; Stewardship (theology); Stakeholder; Data management; Corporate governance; Directive; Public engagement; Public consultation; Test (biology); Computer science; Business; Political science; Engineering; Data quality; Public relations; Operations management; Database; Finance; Law","score_opus":0.6550036183699004,"score_gpt":0.5352410799770353,"score_spread":0.1197625383928651,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293242898","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023831455,0.0007117204,0.5725599,0.040839653,0.022216538,0.002961951,0.33604315,0.00009368686,0.0007419521],"genre_scores_gemma":[0.79081,0.0001683936,0.121884786,0.005549961,0.002834376,0.00010335347,0.07625374,0.00006402305,0.002331369],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.993439,0.00028516306,0.0010486554,0.0016155457,0.0033168804,0.0002947556],"domain_scores_gemma":[0.9922219,0.000662947,0.0009164131,0.005359395,0.00066865707,0.00017067707],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.028374372,0.00014957461,0.0001907847,0.00049979595,0.002294542,0.0051016402,0.01870518,0.000025047135,0.00022133408],"category_scores_gemma":[0.011608844,0.00013064599,0.000015096149,0.000673215,0.00029114212,0.014242206,0.0266436,0.00015619765,0.0000034313373],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035824114,0.00039730416,0.036232114,0.00002227717,0.00029666992,0.000009026008,0.0005753921,0.0001724803,0.00039962918,0.14727324,0.70455724,0.10970641],"study_design_scores_gemma":[0.0006665357,0.00004247423,0.002027968,0.0000095273,0.000038380513,0.000038030103,0.0011411132,0.1396458,0.0000060413845,0.006920848,0.8493141,0.00014916994],"about_ca_topic_score_codex":0.00032257597,"about_ca_topic_score_gemma":0.0006112507,"teacher_disagreement_score":0.76697856,"about_ca_system_score_codex":0.000105032,"about_ca_system_score_gemma":0.00036800568,"threshold_uncertainty_score":0.9995451},"labels":[],"label_agreement":null},{"id":"W4293242937","doi":"10.23889/ijpds.v7i3.2103","title":"Associations between dietary patterns and cardiovascular disease risk in Canadian adults: a comparison of partial least squares, reduced rank regression and the simplified dietary pattern technique.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Partial least squares regression; Medicine; Multivariate statistics; Environmental health; Regression analysis; Proportional hazards model; Refined grains; Obesity; Food group; Hazard ratio; Mathematics; Demography; Statistics; Food science; Biology; Confidence interval; Internal medicine; Whole grains","score_opus":0.06421553134004764,"score_gpt":0.36580869326747406,"score_spread":0.3015931619274264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293242937","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9837842,0.0010620246,0.00063463364,0.004677788,0.00035376422,0.0006848167,0.008784252,0.000007096003,0.000011443947],"genre_scores_gemma":[0.99731743,0.00032049813,0.00017422058,0.00009012931,0.00019959484,0.00004614121,0.0018427802,0.0000066158013,0.0000025783038],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980248,0.00011831269,0.00045882913,0.00029999556,0.0009037447,0.00019432459],"domain_scores_gemma":[0.9989012,0.00016012456,0.00026086977,0.0002604096,0.00021394217,0.00020348789],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018583147,0.00009336374,0.00027071053,0.00024611485,0.0007677483,0.000059417853,0.00039430553,0.000021498396,0.000013940551],"category_scores_gemma":[0.000711472,0.00006998413,0.00008683739,0.00018033138,0.0001582233,0.00033169365,0.0003384868,0.0002544747,1.16059006e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043661345,0.000058110603,0.98281276,0.000012360403,0.00013036246,0.00000850206,0.00014925118,0.00026565045,0.000016084547,0.000065514905,0.00033125022,0.015713543],"study_design_scores_gemma":[0.0022592372,0.00007504245,0.98045975,0.0001310859,0.00014428394,0.00002049248,0.0003630007,0.014937987,0.000007891656,0.0005762261,0.0009456744,0.00007934653],"about_ca_topic_score_codex":0.12907498,"about_ca_topic_score_gemma":0.011629412,"teacher_disagreement_score":0.117445566,"about_ca_system_score_codex":0.00020239977,"about_ca_system_score_gemma":0.00016215917,"threshold_uncertainty_score":0.8767246},"labels":[],"label_agreement":null},{"id":"W4293243093","doi":"10.23889/ijpds.v7i3.2102","title":"Development and validation of a cardiovascular disease risk-prediction model using population health surveys and dietary indices: the Cardiovascular Disease Population Risk Tool – Nutrition (CVDPoRT-Nutrition).","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada; Institute for Clinical Evaluative Sciences; Ottawa Hospital; Government of Canada; University of British Columbia","funders":"","keywords":"Medicine; Disease; Population; National Health and Nutrition Examination Survey; Environmental health; Mediterranean diet; Risk assessment; Gerontology; Internal medicine; Computer science","score_opus":0.08852172052019146,"score_gpt":0.34103093262945217,"score_spread":0.2525092121092607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243093","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9646823,0.0051441663,0.024196435,0.00053392316,0.00059368665,0.0012878716,0.0035331056,0.000027133605,0.0000013848155],"genre_scores_gemma":[0.97633284,0.003614734,0.0112087475,0.000067203655,0.00036442417,0.00011292399,0.008275872,0.000019432473,0.0000038313206],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9954429,0.00041960806,0.00087540585,0.0006308611,0.0023809066,0.0002502759],"domain_scores_gemma":[0.9978515,0.0000897898,0.0007303512,0.00052830746,0.0005378011,0.00026227642],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0073101767,0.00019340862,0.00035311776,0.00043218228,0.002451773,0.00015721151,0.00035233985,0.000032751617,0.0000073949277],"category_scores_gemma":[0.00063942,0.00017121763,0.0002301612,0.00040716672,0.00012632832,0.001469974,0.00037775695,0.00025940727,1.9267468e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007766208,0.00072622474,0.619335,0.00036697896,0.0015267761,0.000012409671,0.0002404105,0.31951162,0.000040861487,0.0004039085,0.00022447786,0.056834687],"study_design_scores_gemma":[0.0017875173,0.000071337,0.7283412,0.00017046905,0.00063114683,0.00006626119,0.00020968786,0.26352364,0.000005817154,0.0028034823,0.0022335097,0.00015588859],"about_ca_topic_score_codex":0.0021607254,"about_ca_topic_score_gemma":0.000025716829,"teacher_disagreement_score":0.109006226,"about_ca_system_score_codex":0.0005865377,"about_ca_system_score_gemma":0.00026662555,"threshold_uncertainty_score":0.9988469},"labels":[],"label_agreement":null},{"id":"W4293243551","doi":"10.23889/ijpds.v7i3.2033","title":"Cross-jurisdictional data access processes and coordination in two countries: key learnings and innovative approaches.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Key (lock); Computer science; Data access; Data sharing; Collaborative network; Data science; Process management; Knowledge management; Business; Computer security; Database","score_opus":0.4704630111872487,"score_gpt":0.5899075539934028,"score_spread":0.11944454280615407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243551","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9606424,0.00011433533,0.016184315,0.019899338,0.0010188988,0.000591441,0.0014455189,0.000021954744,0.00008181685],"genre_scores_gemma":[0.9895868,0.00004844887,0.0045214705,0.0007785451,0.0002829819,0.000021377033,0.0046445946,0.000009881553,0.000105943895],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972975,0.000052498428,0.000780591,0.00053592084,0.0011745098,0.00015893245],"domain_scores_gemma":[0.9971972,0.0005619187,0.00062204147,0.0002938711,0.0012420939,0.000082850755],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0053736386,0.00009456214,0.00013612806,0.00049211574,0.00057612587,0.0006477071,0.0010891559,0.00001763766,0.0001227541],"category_scores_gemma":[0.0095436005,0.00009298334,0.00000824928,0.00079012994,0.00023550622,0.007595502,0.0018007525,0.0003423575,8.320811e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006367718,0.00013301641,0.9689255,0.00003435864,0.000038945836,0.000009278836,0.00033386974,0.0011065989,0.000097134274,0.0026861595,0.0023241406,0.02367423],"study_design_scores_gemma":[0.004448431,0.00013005924,0.71414554,0.00005674827,0.0000400443,0.0008613727,0.00080678414,0.21985199,0.00002080098,0.0026654452,0.056784477,0.00018832441],"about_ca_topic_score_codex":0.00040333482,"about_ca_topic_score_gemma":0.00019001414,"teacher_disagreement_score":0.25477996,"about_ca_system_score_codex":0.00025750042,"about_ca_system_score_gemma":0.00076239934,"threshold_uncertainty_score":0.99879944},"labels":[],"label_agreement":null},{"id":"W4293243701","doi":"10.23889/ijpds.v7i3.2099","title":"The geography of overdose in British Columbia.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"BC Centre for Disease Control; University of British Columbia","funders":"","keywords":"Odds; Drug overdose; Environmental health; Medicine; Demography; Geography; Public health; Harm reduction; Logistic regression; Poison control; Medical emergency","score_opus":0.02602587332589366,"score_gpt":0.3511528162432807,"score_spread":0.32512694291738703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243701","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99661463,0.0002135441,0.0001079318,0.0010130996,0.0013066786,0.00023893706,0.00042429366,0.000005214923,0.00007567993],"genre_scores_gemma":[0.998448,0.00011219165,0.00086025044,0.000114017006,0.00005433301,0.00001674922,0.00029246518,0.0000045613333,0.00009743501],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984758,0.000019804667,0.00029703832,0.0001671112,0.00091668166,0.00012359553],"domain_scores_gemma":[0.9992536,0.00006163841,0.00017501903,0.00023791687,0.00022803807,0.000043814303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009470828,0.00003106531,0.00007233359,0.00013427882,0.00044457888,0.00023601395,0.00085983623,0.000007605552,0.0000854198],"category_scores_gemma":[0.00034416287,0.00003620254,0.00004150912,0.00032971724,0.00009456493,0.0004521896,0.00031742532,0.00010860777,4.2284998e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004421008,0.0001622788,0.97471344,0.0000023541709,0.000021954189,0.000013701433,0.000034468496,0.00020237824,0.00006648324,0.00015989767,0.0012711287,0.023307683],"study_design_scores_gemma":[0.0009025266,0.000090128895,0.9824909,0.000023995324,0.000010076611,0.00023090928,0.00021478753,0.004099567,0.0000053620356,0.001698913,0.010196782,0.000036057132],"about_ca_topic_score_codex":0.007111571,"about_ca_topic_score_gemma":0.0038887146,"teacher_disagreement_score":0.023271626,"about_ca_system_score_codex":0.00017184018,"about_ca_system_score_gemma":0.00020542763,"threshold_uncertainty_score":0.99950016},"labels":[],"label_agreement":null},{"id":"W4293243706","doi":"10.23889/ijpds.v7i3.2048","title":"The Canadian Neighbourhood Early Childhood Development (CanNECD) Socioeconomic Index: Stability and Measurement Invariance Over Time.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; University of British Columbia","funders":"","keywords":"Neighbourhood (mathematics); Socioeconomic status; Index (typography); Composite index; Measurement invariance; Statistics; Econometrics; Demography; Confirmatory factor analysis; Geography; Psychology; Mathematics; Computer science; Sociology; Composite indicator; Structural equation modeling","score_opus":0.05164216243366281,"score_gpt":0.32487246029442074,"score_spread":0.2732302978607579,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243706","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95912963,0.0001639259,0.0003425597,0.0309361,0.006572351,0.0007884445,0.00021109177,0.00003433556,0.0018215869],"genre_scores_gemma":[0.9979975,0.000022441922,0.00079179823,0.0006084399,0.00031036767,0.000026201884,0.00005980899,0.000007129414,0.00017628785],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99703497,0.00012348793,0.0004026481,0.00035742376,0.0017006289,0.00038086687],"domain_scores_gemma":[0.9985439,0.00006628049,0.00027177963,0.00025096277,0.00052200304,0.0003450702],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007812699,0.0000958026,0.000083552775,0.00020402767,0.0086747445,0.0013635929,0.0019425966,0.000027131446,0.0003505549],"category_scores_gemma":[0.00080840406,0.00008756573,0.000026617681,0.00019371582,0.00016225222,0.0013891226,0.00037562734,0.00023539797,0.000015067232],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006386143,0.00019206826,0.75781953,0.0000025719582,0.00018063077,0.00000299635,0.04597686,0.00030998728,0.000047720278,0.043823794,0.012760179,0.13881978],"study_design_scores_gemma":[0.00026056357,0.000013281725,0.9062485,0.0000055127766,0.0000034842412,0.0000070370234,0.0017069253,0.00028993154,0.0000058200094,0.0027017177,0.088629685,0.00012754071],"about_ca_topic_score_codex":0.05050642,"about_ca_topic_score_gemma":0.22820167,"teacher_disagreement_score":0.17769524,"about_ca_system_score_codex":0.0031338073,"about_ca_system_score_gemma":0.00995204,"threshold_uncertainty_score":0.99967307},"labels":[],"label_agreement":null},{"id":"W4293243707","doi":"10.23889/ijpds.v7i3.2086","title":"Weeneebayko Area Health Authority-ICES-Laurentian University Collaboration: Working together to support communities with Indigenous Health Research in the James and Hudson Bay Region, in Northeast Ontario, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; Laurentian University","funders":"","keywords":"Indigenous; General partnership; Stewardship (theology); Population health; Public relations; Public health; Environmental planning; Business; Environmental resource management; Geography; Political science; Medicine; Nursing; Ecology","score_opus":0.23113443220100244,"score_gpt":0.4480432496427254,"score_spread":0.21690881744172297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243707","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93774647,0.00007199779,0.00025926298,0.058738094,0.0012375097,0.0013406228,0.000324597,0.000006566095,0.0002749127],"genre_scores_gemma":[0.99627364,0.000058440117,0.0004028166,0.0024926006,0.00009597929,0.000028361083,0.0004067429,0.0000066390185,0.00023476651],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9966355,0.0009605659,0.000440616,0.00025045886,0.0010036465,0.0007092433],"domain_scores_gemma":[0.99838006,0.00033183803,0.00033447266,0.00029169564,0.0005330251,0.00012890449],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.009180541,0.00008697652,0.0001757704,0.00056868995,0.011680783,0.00008967918,0.0013899225,0.0000254135,0.00007909537],"category_scores_gemma":[0.00007602235,0.000072906405,0.000008950184,0.0009950368,0.00009841025,0.0004482248,0.0007271971,0.0009117809,4.94503e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00017190805,0.000049250215,0.81754506,0.000010019184,0.000009383414,0.000023072878,0.17106009,0.0007353921,8.107322e-8,0.0011154115,0.007575873,0.0017044697],"study_design_scores_gemma":[0.00049848785,0.00034616372,0.4022085,0.00008299366,0.0000017248149,0.000056961722,0.42133182,0.00024982085,1.7840224e-8,0.00015156511,0.17499207,0.0000798649],"about_ca_topic_score_codex":0.96322054,"about_ca_topic_score_gemma":0.9998317,"teacher_disagreement_score":0.41533655,"about_ca_system_score_codex":0.0057425564,"about_ca_system_score_gemma":0.012578256,"threshold_uncertainty_score":0.99807423},"labels":[],"label_agreement":null},{"id":"W4293243708","doi":"10.23889/ijpds.v7i3.2037","title":"Pandemic effects on health condition specific healthcare encounters in British Columbia, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ministry of Health","funders":"","keywords":"Pandemic; Population; Health care; Socioeconomic status; Public health; Medicine; Anxiety; Gerontology; Psychology; Demography; Environmental health; Psychiatry; Coronavirus disease 2019 (COVID-19); Disease; Nursing; Political science","score_opus":0.08150570737170783,"score_gpt":0.4592699955966794,"score_spread":0.3777642882249716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9025166,0.0004822818,0.00042788146,0.058039255,0.030475834,0.0019008517,0.0058396743,0.000059359038,0.00025827545],"genre_scores_gemma":[0.9530497,0.0002860094,0.00027200935,0.04297635,0.0006346554,0.0001052404,0.0022207424,0.0000156352,0.00043961595],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99617743,0.00038347344,0.0008573713,0.00045328584,0.0015545657,0.00057389104],"domain_scores_gemma":[0.99792343,0.00055670895,0.0006234331,0.00033039087,0.0003262559,0.00023975022],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0034790493,0.00008510605,0.0002270212,0.0002635687,0.0030815916,0.0001570525,0.0014750247,0.000035375848,0.00034637382],"category_scores_gemma":[0.00042558546,0.00012607125,0.000031574862,0.0003958201,0.000041777224,0.00086830044,0.0004077152,0.00084645476,0.00000482833],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00005902541,0.000038354927,0.61798036,0.000060703107,0.0000074930754,0.000038217848,0.00020207297,0.000121206176,0.000013637111,0.00040855317,0.33150372,0.049566627],"study_design_scores_gemma":[0.0011429976,0.00013520847,0.6947409,0.00015998968,0.000001660734,0.000078333316,0.00078839704,0.00036486014,3.1494102e-7,0.0012334579,0.30122918,0.00012473504],"about_ca_topic_score_codex":0.8532462,"about_ca_topic_score_gemma":0.98177284,"teacher_disagreement_score":0.12852667,"about_ca_system_score_codex":0.0102627715,"about_ca_system_score_gemma":0.009291806,"threshold_uncertainty_score":0.9982163},"labels":[],"label_agreement":null},{"id":"W4293243715","doi":"10.23889/ijpds.v7i3.2077","title":"Analysing Siamese Neural Network Architectures for Computing Name Similarity.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Similarity (geometry); Computer science; Classifier (UML); False positive paradox; Artificial intelligence; String metric; Artificial neural network; Random forest; Similitude; False positives and false negatives; Set (abstract data type); Machine learning; Pattern recognition (psychology); Data mining; String searching algorithm; Pattern matching","score_opus":0.2782177487324201,"score_gpt":0.5106037761682547,"score_spread":0.23238602743583459,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243715","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27509695,0.00009608599,0.6992705,0.011610349,0.010762718,0.0006318418,0.002284129,0.000049731043,0.00019769785],"genre_scores_gemma":[0.9677878,0.0000015326136,0.028767914,0.0016722338,0.00090530724,0.000008665075,0.00063224783,0.000008250809,0.00021604403],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9944961,0.00019511355,0.00089696504,0.00067727064,0.0033574225,0.00037709574],"domain_scores_gemma":[0.9965632,0.0011482952,0.000778234,0.0007244835,0.0006561311,0.00012966518],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.01694581,0.00011643021,0.0001904095,0.00060978066,0.002467159,0.0018791666,0.0068138726,0.000016075159,0.00017532219],"category_scores_gemma":[0.006043157,0.00009992385,0.0001303243,0.0008947331,0.00014021223,0.0012295324,0.002741666,0.00023273376,0.0000036105769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012432504,0.000051865474,0.01074011,0.0000021043952,0.000039605507,0.000005322761,0.00019787726,0.80004853,0.000034244753,0.011517566,0.024053928,0.1531845],"study_design_scores_gemma":[0.00036220637,0.00005589077,0.018498404,0.0000067240103,0.000015977035,0.00005693482,0.0003757065,0.8098908,0.0000031931902,0.060384225,0.110222,0.00012791311],"about_ca_topic_score_codex":0.000082907136,"about_ca_topic_score_gemma":0.00008549764,"teacher_disagreement_score":0.69269085,"about_ca_system_score_codex":0.00017856614,"about_ca_system_score_gemma":0.00012443132,"threshold_uncertainty_score":0.99915695},"labels":[],"label_agreement":null},{"id":"W4293243725","doi":"10.23889/ijpds.v7i3.2100","title":"Engagement of persons with lived experience in research that uses linked administrative health data - the BC Provincial Overdose Cohort.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Centre for Disease Control; University of British Columbia","funders":"","keywords":"Public health; Medicine; Drug overdose; Declaration; Opioid overdose; Cohort; Medical emergency; Psychiatry; Family medicine; Environmental health; Poison control; Political science; Nursing","score_opus":0.9471365289685427,"score_gpt":0.7684861845089768,"score_spread":0.17865034445956596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95677453,0.000022784681,0.0019604203,0.031931117,0.001758065,0.0029938251,0.0043591247,0.000017294247,0.00018286647],"genre_scores_gemma":[0.99343646,0.00003495694,0.0030116905,0.0023541863,0.00024687036,0.00029869712,0.00045127975,0.000010731025,0.0001551125],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9912877,0.0022181512,0.0011176781,0.00067658746,0.003976961,0.0007229348],"domain_scores_gemma":[0.9938741,0.002680161,0.0012153612,0.0011230602,0.0008817596,0.00022556665],"candidate_categories":["metaresearch","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.033769432,0.00011466221,0.0001982696,0.0006054596,0.0049468353,0.00014278312,0.006195348,0.000024652018,0.0003844127],"category_scores_gemma":[0.0064144344,0.000083342355,0.000018684992,0.0012085367,0.0005949257,0.002604144,0.0030447876,0.0010607644,0.0000041391513],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000516274,0.00019574972,0.89484864,0.000046698788,0.000028548056,0.0000102403965,0.076041065,0.0003949987,0.00026120205,0.00556527,0.017786643,0.0043046917],"study_design_scores_gemma":[0.0015466549,0.00048054015,0.7980983,0.00015797457,0.0000064137566,0.000033393466,0.10319546,0.013538884,0.00002388704,0.0004510379,0.08229701,0.00017043187],"about_ca_topic_score_codex":0.009033129,"about_ca_topic_score_gemma":0.00605802,"teacher_disagreement_score":0.09675031,"about_ca_system_score_codex":0.0013129443,"about_ca_system_score_gemma":0.008612239,"threshold_uncertainty_score":0.9991816},"labels":[],"label_agreement":null},{"id":"W4293243730","doi":"10.23889/ijpds.v7i3.2104","title":"Adherence to emerging plant-based dietary patterns and its association with cardiovascular disease risk in a nationally representative sample of Canadian adults.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Quartile; National Health and Nutrition Examination Survey; Environmental health; Demography; Food frequency questionnaire; Population; Multivariate analysis; Disease; Multivariate statistics; Gerontology; Confidence interval; Internal medicine; Statistics","score_opus":0.02505816892360674,"score_gpt":0.2850483929399714,"score_spread":0.2599902240163647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243730","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9936963,0.000023337983,0.0007878801,0.0007998177,0.00016367479,0.0003375717,0.0041728313,0.0000036512706,0.000014981962],"genre_scores_gemma":[0.9981503,0.000020248519,0.0011230952,0.00009759879,0.000024608278,0.000029582898,0.0005326556,0.000004437697,0.000017468485],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99774325,0.00008269531,0.00024118298,0.00036785827,0.0013589693,0.0002060464],"domain_scores_gemma":[0.9992056,0.00011311654,0.0002061475,0.00019115297,0.00006035322,0.00022362778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014768705,0.0000825196,0.000096249525,0.00030721657,0.0004043918,0.000057179794,0.0006626712,0.000013220841,0.0001845687],"category_scores_gemma":[0.0010286121,0.00007227372,0.000036969624,0.00053291087,0.0000429674,0.0010992306,0.00031560118,0.00013775621,0.0000011605769],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012350737,0.00003551669,0.75873256,0.0000028245515,0.000021846923,0.0000074294703,0.00043680338,0.23878086,0.0000314795,0.000020540043,0.00010758115,0.001699051],"study_design_scores_gemma":[0.0003966281,0.00009967531,0.95165527,0.000018439676,0.000018208182,0.000007139279,0.0007608779,0.04571311,0.000024283252,0.00015511758,0.0010511932,0.000100042555],"about_ca_topic_score_codex":0.21347718,"about_ca_topic_score_gemma":0.08507907,"teacher_disagreement_score":0.19306773,"about_ca_system_score_codex":0.0013714801,"about_ca_system_score_gemma":0.00010767818,"threshold_uncertainty_score":0.9316158},"labels":[],"label_agreement":null},{"id":"W4293243732","doi":"10.23889/ijpds.v7i3.2091","title":"A population-based approach to assessing diabetes management during COVID-19: insights from population data in Ontario, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Capitation; Population; Medicine; Pandemic; Diabetes mellitus; Health care; Family medicine; Environmental health; Coronavirus disease 2019 (COVID-19); Disease; Internal medicine","score_opus":0.09527841953936951,"score_gpt":0.37875091861819815,"score_spread":0.28347249907882865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243732","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.987992,0.000032723357,0.0060735987,0.0021423209,0.0016616763,0.0008424387,0.00081532577,0.000038423317,0.00040152197],"genre_scores_gemma":[0.9616501,0.0000014522892,0.008678162,0.0012818248,0.0001771476,0.00005105908,0.028015682,0.000017765524,0.0001268398],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9957927,0.000067367655,0.00066662504,0.0008725752,0.0022715554,0.0003292122],"domain_scores_gemma":[0.9980502,0.00009203518,0.00035417857,0.0010394991,0.00012431311,0.00033976877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089696056,0.00017829203,0.00022317882,0.00088758796,0.0008885147,0.0005612781,0.0023145576,0.000021793532,0.00024026785],"category_scores_gemma":[0.0005421132,0.00018721732,0.00003458818,0.0006412842,0.00003079797,0.0024002013,0.0015301418,0.0002623197,9.0691896e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015383153,0.00021872412,0.84770757,0.000050050905,0.00007693576,0.000055716788,0.00008408251,0.14734623,0.00006239408,0.0018919186,0.001458369,0.00089417695],"study_design_scores_gemma":[0.001397867,0.000015241892,0.8448496,0.00006551658,0.000054833352,0.0000078087305,0.00036811052,0.14784311,0.0000021352164,0.0008667147,0.004353239,0.0001758387],"about_ca_topic_score_codex":0.82046515,"about_ca_topic_score_gemma":0.7491479,"teacher_disagreement_score":0.07131723,"about_ca_system_score_codex":0.006949129,"about_ca_system_score_gemma":0.0019285437,"threshold_uncertainty_score":0.996863},"labels":[],"label_agreement":null},{"id":"W4293243736","doi":"10.23889/ijpds.v7i3.2064","title":"The Impact of the COVID-19 Pandemic on End-of-Life Prescribing in Ontario Nursing Homes.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo; Canadian Institute for Health Information; McMaster University; Alberta Health Services; University Health Network; Ottawa Hospital; Bruyère","funders":"","keywords":"Medicine; Pandemic; Medical prescription; Coronavirus disease 2019 (COVID-19); Nursing homes; Retrospective cohort study; Outbreak; Demography; Family medicine; Emergency medicine; Nursing; Disease; Internal medicine","score_opus":0.25986345337940175,"score_gpt":0.5191243138093234,"score_spread":0.2592608604299217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9910383,0.000061183055,0.00039799232,0.0024537023,0.005246595,0.00034078685,0.00025275513,0.0000058890123,0.00020279306],"genre_scores_gemma":[0.9994073,0.000012410849,0.000079520825,0.0001314975,0.00010955988,0.000009323585,0.00006642935,0.0000047558283,0.00017918376],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979239,0.00021227158,0.00055770285,0.00017075238,0.0009182017,0.00021717121],"domain_scores_gemma":[0.9980169,0.0006838841,0.00066663965,0.0003434355,0.00020436979,0.000084785366],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0033664869,0.000063460815,0.000111428504,0.00023907104,0.0016393891,0.000035643625,0.0017863449,0.00002249128,0.00016183406],"category_scores_gemma":[0.0021179977,0.000038134818,0.0000779353,0.00034879867,0.00015230615,0.00038744716,0.00032530472,0.00049160625,5.272482e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034559198,0.000056562614,0.97037965,0.0000035485698,0.0000148122945,4.6793483e-7,0.003619868,0.012360533,0.00020806416,0.0017783735,0.0067881634,0.0044443514],"study_design_scores_gemma":[0.0008002545,0.000085000764,0.98251736,0.00009326476,0.000007735061,0.000024455445,0.0022490895,0.0031301263,0.0000031837355,0.004200642,0.006829462,0.000059394813],"about_ca_topic_score_codex":0.0553001,"about_ca_topic_score_gemma":0.034215037,"teacher_disagreement_score":0.021085065,"about_ca_system_score_codex":0.002857729,"about_ca_system_score_gemma":0.003748638,"threshold_uncertainty_score":0.9996603},"labels":[],"label_agreement":null},{"id":"W4293243741","doi":"10.23889/ijpds.v7i3.2093","title":"Addressing multi-region data linkage needs through data sharing agreements – Three Canadian initiatives.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Data sharing; Data governance; Data access; Business; Government (linguistics); Negotiation; Data management; Legislature; Data Protection Act 1998; Knowledge management; Public relations; Computer science; Political science; Computer security; Data quality; Marketing; Database","score_opus":0.6812618955544616,"score_gpt":0.587719947910894,"score_spread":0.0935419476435676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243741","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12767614,0.0023575006,0.41807833,0.1562334,0.12200018,0.008039759,0.14470053,0.00051118975,0.02040298],"genre_scores_gemma":[0.90043396,0.00021950559,0.024377605,0.021597385,0.0021910248,0.000050926254,0.050486602,0.00005022538,0.0005927774],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9958909,0.00016210145,0.0009433036,0.0008624989,0.0014251117,0.0007160552],"domain_scores_gemma":[0.995417,0.00028033412,0.00077554764,0.002668071,0.0005273416,0.000331694],"candidate_categories":["sts","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0049846824,0.00016591111,0.00021315455,0.00070824224,0.0060247695,0.00027660464,0.014799568,0.00006286801,0.0005509695],"category_scores_gemma":[0.001803589,0.00016264644,0.000028812914,0.00063034525,0.000106412626,0.0107489,0.011941456,0.00094816025,0.000025684425],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012393287,0.0001195699,0.8197958,0.000069233494,0.00012259408,0.000082994084,0.0023127582,0.0003565563,0.00005298152,0.008438949,0.13943897,0.029085683],"study_design_scores_gemma":[0.0019323665,0.00004629353,0.34965605,0.00018445331,0.00004658486,0.00009196803,0.002121131,0.14446631,0.0000011813363,0.0022138592,0.49887797,0.0003618591],"about_ca_topic_score_codex":0.061486397,"about_ca_topic_score_gemma":0.10247576,"teacher_disagreement_score":0.7727578,"about_ca_system_score_codex":0.002033522,"about_ca_system_score_gemma":0.0046185455,"threshold_uncertainty_score":0.99604976},"labels":[],"label_agreement":null},{"id":"W4293243782","doi":"10.23889/ijpds.v7i3.2068","title":"Mapping where patients access primary care providers.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Referral; Primary care; Health care; Rural area; Geographic information system; Family medicine; Medicine; Geography; Cartography","score_opus":0.14636745797480855,"score_gpt":0.5001868040659115,"score_spread":0.353819346091103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243782","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7739124,0.0014110163,0.015276513,0.059904523,0.10578739,0.0069512636,0.012035377,0.00038830205,0.024333257],"genre_scores_gemma":[0.9506949,0.00014172781,0.006171567,0.03031804,0.0019202201,0.00025803302,0.008802099,0.000044211756,0.0016491775],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99678284,0.00014613898,0.000687011,0.00039877207,0.0015618644,0.0004233571],"domain_scores_gemma":[0.99746007,0.00019423015,0.00063255505,0.00041973675,0.0011400217,0.0001534094],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0015685247,0.000106340296,0.00015369925,0.00046494082,0.0041457703,0.00018509504,0.0036408347,0.00003530912,0.0004992354],"category_scores_gemma":[0.000429193,0.00009983198,0.000049960832,0.00038127103,0.000054250955,0.0040153023,0.0027482288,0.0005689676,0.000014741868],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011503981,0.000051160172,0.85005563,0.000120122946,0.000018379878,0.000004564815,0.0015910032,0.00017601141,0.000027521373,0.0007970762,0.10632407,0.04071941],"study_design_scores_gemma":[0.0010253245,0.0000443825,0.4955225,0.000046841178,0.000005904174,0.000007446112,0.0016065531,0.0005518453,7.6068807e-7,0.00071459095,0.5003468,0.00012710107],"about_ca_topic_score_codex":0.00048009693,"about_ca_topic_score_gemma":0.0001748644,"teacher_disagreement_score":0.39402267,"about_ca_system_score_codex":0.003092436,"about_ca_system_score_gemma":0.0025725781,"threshold_uncertainty_score":0.9971507},"labels":[],"label_agreement":null},{"id":"W4293243798","doi":"10.23889/ijpds.v7i3.2097","title":"Development of a Prediction Model for Survival Time in Esophageal Cancer Patients Treated with Resection.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Esophageal Cancer Research and Treatment","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa; University of Toronto; Dalhousie University; McGill University; Queen's University; University of Manitoba","funders":"","keywords":"Medicine; Statistic; Cohort; Cancer registry; Stage (stratigraphy); Esophageal cancer; Clinical trial; Internal medicine; Proportional hazards model; Cancer; Oncology; Surgery; Statistics","score_opus":0.07265387944182489,"score_gpt":0.39645902509439124,"score_spread":0.32380514565256635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243798","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917574,0.000055829347,0.0045958282,0.00023014775,0.0003320209,0.0007600225,0.002231202,0.000009844289,0.000027736323],"genre_scores_gemma":[0.98990107,0.000007329949,0.00766157,0.00002201243,0.00006659741,0.00017312248,0.0018318647,0.000008671776,0.00032776964],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99804205,0.000016238255,0.00033648228,0.00024896392,0.0011861009,0.00017018708],"domain_scores_gemma":[0.9989575,0.000030889758,0.00017989085,0.00013313715,0.0006104182,0.000088129964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078010507,0.000069192676,0.00011586688,0.00039004578,0.00031117187,0.000034636967,0.00038097115,0.0000125859415,0.00005380683],"category_scores_gemma":[0.00011988027,0.000056096156,0.000024935753,0.00029163808,0.00004337918,0.0005734115,0.00013361723,0.00010202382,3.7232692e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0062634964,0.00081228284,0.9562672,0.000027372615,0.00014532405,0.000009569414,0.00040263627,0.021814723,0.00065991626,0.00021496341,0.00050983694,0.012872689],"study_design_scores_gemma":[0.00510958,0.00067915,0.49050513,0.000057282155,0.00002455994,0.000020792571,0.000032697582,0.5026463,0.00047243948,0.000114589915,0.00027096295,0.000066519766],"about_ca_topic_score_codex":0.000159666,"about_ca_topic_score_gemma":0.00024265329,"teacher_disagreement_score":0.4808316,"about_ca_system_score_codex":0.0010132989,"about_ca_system_score_gemma":0.0007779986,"threshold_uncertainty_score":0.26497415},"labels":[],"label_agreement":null},{"id":"W4293243809","doi":"10.23889/ijpds.v7i3.2051","title":"Using Primary care data metrics to inform policy and practice: Human Health Resource implications.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Health care; Business; Medicine; Population health; Population; Primary care; Nursing; Medical home; Family medicine; Environmental health; Political science","score_opus":0.44337304771794456,"score_gpt":0.6326986357583577,"score_spread":0.18932558804041316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243809","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07482888,0.0035660528,0.06875761,0.7579916,0.014678078,0.008328558,0.046350315,0.00035062124,0.025148302],"genre_scores_gemma":[0.43790555,0.0005076018,0.19356422,0.32244638,0.0052887104,0.00017168204,0.03871675,0.00010267098,0.0012964352],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965663,0.00024831033,0.00089132495,0.0005055807,0.0013145107,0.00047396944],"domain_scores_gemma":[0.99599254,0.0007441905,0.0009065318,0.0010930989,0.0009088802,0.0003547529],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.006671321,0.000113450726,0.00019284483,0.0011708431,0.007667489,0.00017645748,0.0034622215,0.000034962868,0.000046045694],"category_scores_gemma":[0.0044865566,0.00011329085,0.000021749453,0.001304121,0.00006492881,0.0034727424,0.005584587,0.0005318455,0.00000418695],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00061108783,0.00021671088,0.13558473,0.00040583298,0.0001164772,0.000010179271,0.010374085,0.0013534748,0.00056954013,0.12152003,0.32377195,0.4054659],"study_design_scores_gemma":[0.0005010561,0.0000821437,0.094654284,0.0000318725,0.000012893359,0.00012909016,0.002693531,0.0007691656,3.1542137e-7,0.00066500844,0.90033615,0.00012447362],"about_ca_topic_score_codex":0.0024223775,"about_ca_topic_score_gemma":0.00027015468,"teacher_disagreement_score":0.5765642,"about_ca_system_score_codex":0.004911378,"about_ca_system_score_gemma":0.0067293923,"threshold_uncertainty_score":0.9989086},"labels":[],"label_agreement":null},{"id":"W4293243840","doi":"10.23889/ijpds.v7i3.2083","title":"Evidence from an Applied Health Research Question (AHRQ): Health care utilization of publicly funded rehab services for patients post COVID-19 diagnosis.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Long-Term Effects of COVID-19","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Rehabilitation; Cohort; Acute care; Health care; Cohort study; Residence; Comorbidity; Coronavirus disease 2019 (COVID-19); Emergency medicine; Family medicine; Physical therapy; Demography; Internal medicine; Disease","score_opus":0.22715426832568836,"score_gpt":0.5349856225691102,"score_spread":0.30783135424342184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243840","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86476326,0.0010159629,0.025017526,0.09257434,0.002977501,0.0054107406,0.008131691,0.000096161835,0.000012799193],"genre_scores_gemma":[0.9647169,0.0001810663,0.009087074,0.007601238,0.00034717488,0.00022702961,0.017807337,0.000023822111,0.000008322019],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9941482,0.00042049325,0.00091287936,0.0007857587,0.003291907,0.00044077897],"domain_scores_gemma":[0.9924299,0.001510726,0.0011071076,0.0007588313,0.0034818393,0.00071155874],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.007993821,0.00015523504,0.0003024743,0.0010820178,0.0016563855,0.00034754575,0.0021432752,0.00004607696,0.000078841345],"category_scores_gemma":[0.010071012,0.00015236065,0.00006757552,0.0007874863,0.00016448699,0.0030932787,0.000679106,0.0003120254,0.0000014299983],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037184784,0.0009641069,0.902741,0.001062765,0.00007188531,0.0000039735464,0.0048515475,0.0037956794,0.000363355,0.005513168,0.008680348,0.068233676],"study_design_scores_gemma":[0.005974365,0.005448595,0.9234484,0.0010407206,0.000046013778,0.000040377967,0.0034502167,0.03023578,0.00016782766,0.0042498484,0.02554081,0.0003570699],"about_ca_topic_score_codex":0.0119849425,"about_ca_topic_score_gemma":0.00310612,"teacher_disagreement_score":0.09995366,"about_ca_system_score_codex":0.0031796212,"about_ca_system_score_gemma":0.003241755,"threshold_uncertainty_score":0.9996433},"labels":[],"label_agreement":null},{"id":"W4293243843","doi":"10.23889/ijpds.v7i3.2076","title":"Linking Eight Decades of Canadian Census Collections.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Census; Data science; Computer science; Leverage (statistics); Population; Record linkage; Demographics; Data quality; Linkage (software); Geography; Data mining; Demography; Machine learning; Sociology; Business; Marketing","score_opus":0.09637734138154412,"score_gpt":0.4084209961291392,"score_spread":0.31204365474759505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243843","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7654631,0.00054527266,0.02266016,0.047149014,0.041612446,0.0016398769,0.03550198,0.00012926749,0.08529888],"genre_scores_gemma":[0.9933796,0.000073522315,0.004525535,0.00013708511,0.00035621412,0.000004511235,0.0007228761,0.0000041483836,0.00079649786],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99808824,0.000075433076,0.00028817976,0.00019866426,0.0011333777,0.00021610655],"domain_scores_gemma":[0.99895674,0.00010466801,0.0002454911,0.00018698304,0.000348169,0.00015797337],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0029823063,0.000043955,0.0000731919,0.0016407607,0.0042581055,0.00040589587,0.0022887401,0.000011524686,0.00025097057],"category_scores_gemma":[0.00088380696,0.000045559384,0.00004427512,0.0017942567,0.00016507336,0.0013183581,0.0003103806,0.00012730068,8.262798e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008651612,0.00023040157,0.23385431,0.0000084642215,0.00020441633,0.00003008728,0.007354159,0.015039746,0.0018270463,0.52459043,0.076101586,0.14067282],"study_design_scores_gemma":[0.00013997295,0.000015816122,0.009987113,0.000014129818,0.000013575483,0.00001865809,0.0015414464,0.010035214,0.000023064165,0.004650411,0.97347397,0.00008665642],"about_ca_topic_score_codex":0.113305114,"about_ca_topic_score_gemma":0.1567991,"teacher_disagreement_score":0.89737236,"about_ca_system_score_codex":0.00036659787,"about_ca_system_score_gemma":0.00086241664,"threshold_uncertainty_score":0.9970382},"labels":[],"label_agreement":null},{"id":"W4293243853","doi":"10.23889/ijpds.v7i3.2065","title":"COVID-19 vaccination rates and related outcomes in adults with intellectual and developmental disabilities (IDD): An application of linked administrative health data to support Ontario’s COVID-19 response .","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Vaccination; Medicine; Population; Pandemic; Coronavirus disease 2019 (COVID-19); Christian ministry; Cohort; Young adult; Demography; Environmental health; Gerontology; Immunology","score_opus":0.16999992792894458,"score_gpt":0.4729191074440708,"score_spread":0.3029191795151262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243853","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98276895,0.000017842385,0.0034580505,0.011159147,0.00015223626,0.001155416,0.0012335583,0.000019764453,0.000035043777],"genre_scores_gemma":[0.9907271,0.000014217308,0.0031235297,0.00094201305,0.000015301755,0.00004777409,0.0049681887,0.0000079173415,0.00015394446],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997786,0.000116557916,0.00057691295,0.00055752223,0.00079806044,0.00016498404],"domain_scores_gemma":[0.9981793,0.0005622213,0.0003022288,0.00036802748,0.000146751,0.00044143677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028999902,0.00011970733,0.00019632756,0.00052450626,0.00038021305,0.00012303995,0.000770639,0.000018132248,0.00033805263],"category_scores_gemma":[0.006746036,0.00010731413,0.000011857197,0.00034269865,0.00016956133,0.0015277291,0.00071100134,0.00015226455,6.6431295e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.018354379,0.00074410933,0.92049307,0.00022613995,0.00014462593,0.000029318391,0.0410641,0.0019719268,0.00015591677,0.004367076,0.0026856824,0.009763649],"study_design_scores_gemma":[0.004774961,0.0018552869,0.9326177,0.00005378618,0.000031151823,0.00045544578,0.035075396,0.01768042,0.0000060336406,0.0010992538,0.006146068,0.0002044804],"about_ca_topic_score_codex":0.0053501595,"about_ca_topic_score_gemma":0.024064437,"teacher_disagreement_score":0.018714277,"about_ca_system_score_codex":0.0022108261,"about_ca_system_score_gemma":0.0050872285,"threshold_uncertainty_score":0.99374384},"labels":[],"label_agreement":null},{"id":"W4293243882","doi":"10.23889/ijpds.v7i3.2026","title":"Federated Learning for cross-jurisdictional analyses: A case study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Software deployment; Leverage (statistics); Data sharing; Federated learning; Identification (biology); Machine learning; Artificial intelligence; Data science","score_opus":0.7203096947109929,"score_gpt":0.7122980366271027,"score_spread":0.00801165808389026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293243882","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9640206,0.000026758933,0.03009378,0.0022784704,0.0023505136,0.00075593253,0.0003436062,0.000033395016,0.00009690818],"genre_scores_gemma":[0.9928333,0.000009796808,0.0040411665,0.00029130818,0.0006140743,0.000075253185,0.0006210487,0.000015170671,0.0014988944],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99544543,0.0000938533,0.0006855728,0.00054495316,0.0029599587,0.00027025645],"domain_scores_gemma":[0.9941335,0.0021026465,0.00033167267,0.0002918258,0.0029292114,0.00021116917],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.011679822,0.0000942923,0.00016165493,0.00051762204,0.0030021372,0.0006769315,0.0011196664,0.00004320237,0.0002967743],"category_scores_gemma":[0.017508239,0.00008656806,0.00009996513,0.0005174174,0.0001922139,0.0010466041,0.00088662416,0.0011733336,0.000003024174],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034554424,0.002267866,0.90646344,0.00005093855,0.000696469,0.0025118578,0.00090411154,0.048013963,0.0030436083,0.00526429,0.0031132717,0.024214732],"study_design_scores_gemma":[0.00824455,0.0029201112,0.11640163,0.00006620493,0.00015640502,0.020943945,0.006256646,0.8140769,0.00009217326,0.012001072,0.018492445,0.00034789578],"about_ca_topic_score_codex":0.00036509754,"about_ca_topic_score_gemma":0.00017524995,"teacher_disagreement_score":0.79006183,"about_ca_system_score_codex":0.0005260009,"about_ca_system_score_gemma":0.0011217631,"threshold_uncertainty_score":0.99829584},"labels":[],"label_agreement":null},{"id":"W4294242844","doi":"10.23889/ijpds.v7i3.1783","title":"Marginal structural models using calibrated weights with SuperLearner: application to longitudinal diabetes cohort.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Machine learning; Medicine; Diabetes mellitus; Artificial intelligence; Cohort; Population; Covariate; Marginal structural model; Computer science; Confounding; Econometrics; Mathematics; Internal medicine; Environmental health","score_opus":0.05392972325002019,"score_gpt":0.36654935791921506,"score_spread":0.31261963466919485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294242844","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49454558,0.000015714784,0.50219256,0.0018029838,0.00096536713,0.00029976273,0.00011216912,0.000050390157,0.00001549504],"genre_scores_gemma":[0.89066267,0.0000011373329,0.10851395,0.0002861385,0.00021258117,0.00003026352,0.0002529084,0.000012379523,0.000027995324],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99649405,0.000104334744,0.000406832,0.00074838154,0.0018630621,0.00038334946],"domain_scores_gemma":[0.9980167,0.00007856939,0.00032166243,0.0006939327,0.0006604001,0.00022872459],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0014745479,0.00014863904,0.0001443022,0.00053865364,0.0015554479,0.00081679266,0.0048959143,0.000021530213,0.000035104356],"category_scores_gemma":[0.00012813504,0.00013069289,0.000032308933,0.0009505699,0.00007123314,0.0046781325,0.0014115283,0.00033877176,0.0000019837057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048155667,0.000019680783,0.42221344,0.000004857037,0.000023027653,0.000007148148,0.00016255288,0.528224,0.00038223108,0.042461075,0.000106731175,0.006347096],"study_design_scores_gemma":[0.00021346114,0.00009530902,0.10367955,0.000013121176,0.000006478625,0.0002296641,0.000020316385,0.8905693,0.00002725702,0.0041329297,0.00085044093,0.00016213901],"about_ca_topic_score_codex":0.0007215214,"about_ca_topic_score_gemma":0.000046575937,"teacher_disagreement_score":0.39611706,"about_ca_system_score_codex":0.0005148904,"about_ca_system_score_gemma":0.0003832598,"threshold_uncertainty_score":0.9997444},"labels":[],"label_agreement":null},{"id":"W4294242860","doi":"10.23889/ijpds.v7i3.1923","title":"Changes in social support and the emotional health of immigrant, refugee, and non-immigrant children across middle childhood: A three year follow up study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Immigration; Refugee; Sadness; Acculturation; Psychology; Social support; Life satisfaction; Mental health; Developmental psychology; Medicine; Clinical psychology; Social psychology; Psychiatry; Geography","score_opus":0.05803629870776957,"score_gpt":0.4005495676092598,"score_spread":0.34251326890149025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294242860","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99242735,0.000108446424,0.00020700238,0.0038465492,0.0013131625,0.0006958694,0.001380463,0.00000610445,0.0000150673195],"genre_scores_gemma":[0.99864346,0.000030952197,0.00016357249,0.0003618806,0.00027637897,0.000043382148,0.00040637495,0.000008514314,0.000065497385],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99787766,0.00012910135,0.0005294451,0.0003703191,0.0008062653,0.00028718484],"domain_scores_gemma":[0.9989979,0.00008664058,0.00046601702,0.00022125877,0.00014081493,0.00008733115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040628575,0.00010286419,0.00020296246,0.00025927933,0.0011496596,0.00010554136,0.0008534565,0.000024152836,0.000089385336],"category_scores_gemma":[0.00011334085,0.000082238956,0.00003650196,0.0003142582,0.00020926006,0.0004001252,0.000330503,0.00024169146,0.0000011146778],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008616173,0.00037304242,0.9314403,0.000007875206,0.000081083606,0.0000025854843,0.040169902,0.000025423817,0.0000069087305,0.007942652,0.0011022291,0.017986396],"study_design_scores_gemma":[0.0050811064,0.0002952345,0.9874941,0.000010864016,0.0000071305085,0.00014567256,0.0049334588,0.0003868922,5.8952867e-7,0.0011731049,0.00039671894,0.000075098185],"about_ca_topic_score_codex":0.0045134467,"about_ca_topic_score_gemma":0.02319659,"teacher_disagreement_score":0.056053843,"about_ca_system_score_codex":0.00008504575,"about_ca_system_score_gemma":0.00017086424,"threshold_uncertainty_score":0.99462754},"labels":[],"label_agreement":null},{"id":"W4294242873","doi":"10.23889/ijpds.v7i3.2006","title":"Using linked administrative data to evaluate and improve the quality of end-of-life care in nursing homes.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo; McMaster University; Alberta Health Services; University Health Network; University of Toronto; Lakeridge Health; University of Ottawa; Bruyère; Ottawa Hospital","funders":"","keywords":"Nursing; Quality (philosophy); Business; Process management; Psychology; Medicine; Computer science","score_opus":0.4458629691979977,"score_gpt":0.6125949342208298,"score_spread":0.16673196502283205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294242873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9887483,0.00024253193,0.0017369237,0.0021672002,0.0035753595,0.00053400587,0.0029222057,0.0000040358395,0.00006945106],"genre_scores_gemma":[0.99583036,0.0000114896075,0.0034388173,0.00008483586,0.00017159704,0.000007225809,0.0004369667,0.0000049215378,0.00001378616],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976117,0.00029398807,0.00071366236,0.0002799889,0.00092931034,0.00017132344],"domain_scores_gemma":[0.9977819,0.0004174857,0.0006610821,0.0004802921,0.00058542937,0.00007386038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047517163,0.000064065454,0.00015858591,0.00026168078,0.0007340794,0.000034634482,0.0016446448,0.000021706564,0.000046251313],"category_scores_gemma":[0.002018088,0.000051103118,0.000020288579,0.00037869098,0.00013748142,0.00069274177,0.0008465521,0.0002555023,2.3765021e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004833925,0.0005141386,0.50232434,0.0002971565,0.00016125936,0.0000065230265,0.10464065,0.008356752,0.035619583,0.01996928,0.0048396667,0.31843668],"study_design_scores_gemma":[0.002031718,0.00026240275,0.8848305,0.00035583987,0.000047123165,0.000017023072,0.06978591,0.036936704,0.000059641112,0.0028702917,0.0026026987,0.00020014783],"about_ca_topic_score_codex":0.0012695005,"about_ca_topic_score_gemma":0.00060690945,"teacher_disagreement_score":0.38250613,"about_ca_system_score_codex":0.00034696175,"about_ca_system_score_gemma":0.001290715,"threshold_uncertainty_score":0.5646019},"labels":[],"label_agreement":null},{"id":"W4294242881","doi":"10.23889/ijpds.v7i3.1926","title":"Evaluation of low acuity patients discharged from a virtual emergency department at a major urban academic health sciences centre in Toronto, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Health Sciences Centre; Schwartz/Reisman Emergency Medicine Institute; McMaster University; Institute for Clinical Evaluative Sciences; Impact; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Emergency department; Christian ministry; Health care; Propensity score matching; Triage; Family medicine; Emergency medicine; Confounding; Medical emergency; Internal medicine; Nursing","score_opus":0.06151331173152526,"score_gpt":0.41292340888754975,"score_spread":0.3514100971560245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294242881","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9888761,0.0010622903,0.000049751616,0.0020809125,0.0038036013,0.0004792945,0.003570897,0.0000044121925,0.00007272332],"genre_scores_gemma":[0.9973449,0.00022582567,0.00016379109,0.00019482436,0.00015500042,0.000018861267,0.0018438321,0.0000048007264,0.000048150345],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9950593,0.00012395227,0.00065962045,0.00035951595,0.0035619608,0.00023564114],"domain_scores_gemma":[0.9983822,0.000036872265,0.0004975768,0.00018021859,0.00079141045,0.000111694804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030822926,0.00009610867,0.00016535846,0.00013060078,0.00068325555,0.0000128307265,0.0008194685,0.000015051461,0.0007692593],"category_scores_gemma":[0.0010849109,0.00008470174,0.000038448816,0.0002820503,0.000071580325,0.00083664415,0.00051897863,0.00014506748,3.8753973e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017109787,0.00020802324,0.95652294,0.000007365258,0.000072661715,0.0000015199852,0.0007355745,0.0006311639,0.00036341924,0.0004768213,0.030319503,0.010489907],"study_design_scores_gemma":[0.0018563533,0.0002133286,0.97000796,0.00008591116,0.000059713275,0.000006983535,0.0014753935,0.02291608,0.000099742196,0.00036463264,0.0027793495,0.00013458027],"about_ca_topic_score_codex":0.1195966,"about_ca_topic_score_gemma":0.40259853,"teacher_disagreement_score":0.28300193,"about_ca_system_score_codex":0.004068941,"about_ca_system_score_gemma":0.0016608712,"threshold_uncertainty_score":0.99975425},"labels":[],"label_agreement":null},{"id":"W4294242882","doi":"10.23889/ijpds.v7i3.1950","title":"Harnessing the power of data linkage to enrich the cancer research ecosystem in Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal; CancerCare Manitoba; Saskatchewan Cancer Agency; Alberta Health Services; McGill University; University of British Columbia; Nova Scotia Health Authority; Ontario Institute for Cancer Research; Dalhousie University","funders":"","keywords":"Biobank; Data sharing; Record linkage; Cancer registry; Health care; General partnership; Linkage (software); Population health; Population; Business; Medicine; Political science; Environmental health; Bioinformatics; Alternative medicine","score_opus":0.3355970004829542,"score_gpt":0.5101747246973648,"score_spread":0.1745777242144106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294242882","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9636045,0.0003322726,0.0011202475,0.030438267,0.0022669174,0.00044348498,0.0016387412,0.0000031558588,0.00015241021],"genre_scores_gemma":[0.99817866,0.000018275283,0.00057741744,0.00081749045,0.00020442167,0.000017025293,0.00012602365,0.00000460628,0.00005605573],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9965081,0.00010198431,0.00037604474,0.00029285083,0.0024946283,0.00022638153],"domain_scores_gemma":[0.99810153,0.00022520371,0.0001726911,0.0007856004,0.00063905097,0.000075894575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0074420148,0.000050891198,0.00009432061,0.00021070549,0.0006751932,0.00013491187,0.0046191895,0.000008336859,0.00011914019],"category_scores_gemma":[0.0012312261,0.00003138466,0.000014289051,0.00087701477,0.00005545292,0.00085993443,0.0018486221,0.00036458994,6.691274e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010576327,0.000110356006,0.74201405,0.00003264237,0.00011563557,0.00013339828,0.0023964883,0.05094467,0.004885731,0.0047678314,0.110260345,0.08328122],"study_design_scores_gemma":[0.0008589428,0.00011795064,0.6708073,0.00038881504,0.00002515556,0.0005026598,0.009554504,0.14435454,0.00016623312,0.00047405463,0.17259389,0.0001559605],"about_ca_topic_score_codex":0.4696435,"about_ca_topic_score_gemma":0.60813206,"teacher_disagreement_score":0.13848858,"about_ca_system_score_codex":0.0013172644,"about_ca_system_score_gemma":0.0034720723,"threshold_uncertainty_score":0.858368},"labels":[],"label_agreement":null},{"id":"W4294242885","doi":"10.23889/ijpds.v7i3.1861","title":"Early Childhood Exposure to Intimate Partner Violence and Developmental Vulnerability at Kindergarten: Linking Canadian Population-Level Administrative Data.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Intimate Partner and Family Violence","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health; University of Calgary","funders":"","keywords":"Population; Vulnerability (computing); Early childhood; Domestic violence; Medicine; Demography; Social vulnerability; Cohort study; Poison control; Cohort; Logistic regression; Child development; Injury prevention; Occupational safety and health; Neighbourhood (mathematics); Suicide prevention; Psychology; Developmental psychology; Environmental health; Psychiatry; Psychological intervention","score_opus":0.12382601586992564,"score_gpt":0.4082292297723822,"score_spread":0.28440321390245654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294242885","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98731136,0.000053265707,0.0016986749,0.0012511052,0.0031063755,0.0007205689,0.004341384,0.000040777453,0.0014764698],"genre_scores_gemma":[0.9900006,0.000035659763,0.007309544,0.0006245795,0.0003090365,0.000030352427,0.0015684171,0.000011756999,0.00011002378],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9964223,0.00016118144,0.0005256927,0.00077351264,0.0015945161,0.0005227844],"domain_scores_gemma":[0.9982063,0.00014716269,0.00025119208,0.0004534619,0.00044037204,0.0005014823],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0040165274,0.00015839773,0.00015483543,0.0003812851,0.00520285,0.00074971456,0.0033338962,0.00004555714,0.00023447504],"category_scores_gemma":[0.0011850488,0.00016655728,0.000028931445,0.00049491297,0.00024242688,0.002985397,0.0016267209,0.00028026343,0.00001518731],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017012701,0.00018252114,0.848098,0.000008636325,0.000089687564,0.00003817929,0.013785007,0.0020542732,0.0002643859,0.034899045,0.0024048854,0.098005265],"study_design_scores_gemma":[0.00029064892,0.00006674495,0.98306876,0.00006676455,0.000011385619,0.00007250196,0.0018252595,0.0020638262,0.000012191148,0.0024531381,0.009799404,0.00026938814],"about_ca_topic_score_codex":0.051991947,"about_ca_topic_score_gemma":0.041340336,"teacher_disagreement_score":0.13497075,"about_ca_system_score_codex":0.0012216911,"about_ca_system_score_gemma":0.0013175228,"threshold_uncertainty_score":0.99609226},"labels":[],"label_agreement":null},{"id":"W4294242912","doi":"10.23889/ijpds.v7i3.1892","title":"Integrating administrative and clinical datasets to improve patient outcomes.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"St Joseph's Health Care; London Health Sciences Centre; Western University","funders":"","keywords":"Health care; Process (computing); Medical emergency; Electronic health record; Medical record; Acute care; Data sharing; Business; Medicine; Computer science; Alternative medicine","score_opus":0.22937868242990483,"score_gpt":0.5947366517715013,"score_spread":0.3653579693415964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294242912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8125673,0.000084528256,0.011260586,0.09012896,0.048235618,0.003139798,0.03265717,0.000100181154,0.0018258959],"genre_scores_gemma":[0.93950766,0.00002656101,0.018675825,0.037950415,0.00061305723,0.00011571807,0.0027285293,0.00001779828,0.00036444276],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99696004,0.00022499809,0.0010359806,0.00046869795,0.000967322,0.00034298017],"domain_scores_gemma":[0.9974807,0.00078457635,0.0005839868,0.00042942792,0.0004146326,0.00030668182],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0040671355,0.00010863374,0.00020216088,0.00026092827,0.0024951291,0.0001010715,0.0015329192,0.00003325389,0.00024478504],"category_scores_gemma":[0.0034232892,0.00008976173,0.0000439424,0.0002101276,0.000075799755,0.0012568075,0.002236225,0.00066693145,0.000012082099],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034649565,0.00016346102,0.6918268,0.000015102498,0.00006623772,0.000020877507,0.0010738821,0.000026165719,0.00011387939,0.012182121,0.13712546,0.1570395],"study_design_scores_gemma":[0.0012329145,0.00063155097,0.4064641,0.000031300475,0.000021701166,0.00004487277,0.0030517392,0.0027575314,0.0000040923346,0.0017432236,0.5837876,0.00022939304],"about_ca_topic_score_codex":0.00038019658,"about_ca_topic_score_gemma":0.0003576091,"teacher_disagreement_score":0.44666213,"about_ca_system_score_codex":0.0007232966,"about_ca_system_score_gemma":0.0015002827,"threshold_uncertainty_score":0.9988035},"labels":[],"label_agreement":null},{"id":"W4294242943","doi":"10.23889/ijpds.v7i3.1788","title":"Applying the British Columbia Health System Matrix (BCHSM) population segmentation framework to support integrated care in Ontario, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Population; Health care; Business; Medicine; Geography; Gerontology; Environmental health; Economic growth; Economics","score_opus":0.04378822641532004,"score_gpt":0.3746570427536082,"score_spread":0.3308688163382882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294242943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9755265,0.000115030314,0.0071055614,0.0034676562,0.006981775,0.004662577,0.0017680248,0.00006708324,0.00030579272],"genre_scores_gemma":[0.98915863,0.000004030386,0.003265463,0.00093321,0.00014020674,0.00029972696,0.0056411037,0.0000131408115,0.0005445067],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969639,0.000062963416,0.0005945324,0.000389539,0.0017095201,0.00027950061],"domain_scores_gemma":[0.99882597,0.000048164955,0.00033602465,0.00033721063,0.0002979909,0.00015462832],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012105516,0.00008983128,0.00016287489,0.00018743608,0.0014634887,0.0014451985,0.0010060023,0.000017103579,0.00037218223],"category_scores_gemma":[0.00021318241,0.00010708508,0.000034543864,0.0005655032,0.000028292568,0.0007608561,0.0003953362,0.000330759,0.0000011802482],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025082516,0.0001030356,0.8478749,0.000110149565,0.000073521114,0.00013102737,0.00072111085,0.02834488,0.000028259761,0.0016176552,0.054352608,0.066392034],"study_design_scores_gemma":[0.0012225008,0.00021648474,0.909992,0.00040760016,0.000039274066,0.00042848743,0.015396342,0.013321633,0.0000010375254,0.0002828222,0.058490302,0.00020152656],"about_ca_topic_score_codex":0.98839253,"about_ca_topic_score_gemma":0.99693114,"teacher_disagreement_score":0.06619051,"about_ca_system_score_codex":0.011616012,"about_ca_system_score_gemma":0.0040416624,"threshold_uncertainty_score":0.99983644},"labels":[],"label_agreement":null},{"id":"W4294242977","doi":"10.23889/ijpds.v7i3.1932","title":"The impact of not having a primary care provider on emergency department utilization and hospitalizations before and during COVID-19: A novel retrospective cohort study linking primary care waitlists with administrative billing data.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Emergency department; Medicine; Emergency medicine; Ambulatory care; Population; Cohort; Primary care; Family medicine; Medical emergency; Ambulatory; Retrospective cohort study; Cohort study; Health care; Nursing; Environmental health","score_opus":0.07570382592400918,"score_gpt":0.4142377890195635,"score_spread":0.3385339630955543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294242977","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9933539,0.00049148337,0.0013272337,0.00025597189,0.0004090205,0.0012412942,0.002859659,0.000014497484,0.000046913545],"genre_scores_gemma":[0.99461067,0.00027620536,0.0005710306,0.000044135275,0.0001067585,0.00005091525,0.004314954,0.000012684756,0.0000126663745],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99778175,0.000035246656,0.00042903022,0.0005072088,0.0010832087,0.00016354027],"domain_scores_gemma":[0.998121,0.00005380106,0.00042121345,0.00038417606,0.0009084292,0.00011136997],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00067396904,0.00014168643,0.00018659886,0.00018645445,0.0021932095,0.00010379738,0.00052856206,0.000016293034,0.0000055944915],"category_scores_gemma":[0.0004622556,0.000095291136,0.000032557404,0.00031997327,0.00015536332,0.0008804816,0.0007031942,0.00017060642,2.8258423e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003620126,0.00011597334,0.99244636,0.00007590843,0.00019562873,0.000008778195,0.0046405913,0.0007051559,0.00015325623,0.00019753783,0.000029224477,0.001069549],"study_design_scores_gemma":[0.0009434291,0.00092057016,0.98755884,0.00011306626,0.00011207364,0.00009571682,0.0073889415,0.0026112143,0.000015147189,0.000045458975,0.00009198911,0.000103564686],"about_ca_topic_score_codex":0.00021229904,"about_ca_topic_score_gemma":0.00045848882,"teacher_disagreement_score":0.0048875557,"about_ca_system_score_codex":0.0010818802,"about_ca_system_score_gemma":0.0006528919,"threshold_uncertainty_score":0.9991058},"labels":[],"label_agreement":null},{"id":"W4294242987","doi":"10.23889/ijpds.v7i3.1917","title":"Maternal Mental Health, Child Distress and Family Strain During the COVID-19 Pandemic: Linking the Provincial Longitudinal Cohort with the COVID-19 Impact Survey Data in Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal Mental Health During Pregnancy and Postpartum","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Athabasca University; University of Calgary","funders":"","keywords":"Latent class model; Mental health; Cohort; Demography; Odds; Anxiety; Longitudinal study; Medicine; Logistic regression; Depression (economics); Cohort study; Socioeconomic status; Odds ratio; Pandemic; Distress; Psychology; Coronavirus disease 2019 (COVID-19); Clinical psychology; Psychiatry; Environmental health; Population","score_opus":0.10452640270446484,"score_gpt":0.41375949978728854,"score_spread":0.3092330970828237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294242987","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95062286,0.00028910613,0.0003316952,0.029672598,0.00090622896,0.0009128133,0.017249165,0.000009832565,0.000005713557],"genre_scores_gemma":[0.9915673,0.0001291568,0.000041354822,0.0056591746,0.00023047168,0.00002695036,0.0022945276,0.0000109529465,0.000040107934],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967493,0.0002947581,0.0004890118,0.0004543549,0.0016335967,0.00037902396],"domain_scores_gemma":[0.99820983,0.0002887841,0.000469256,0.0006016791,0.00007376888,0.00035665696],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005981895,0.00014965961,0.00016958252,0.000109723194,0.002842555,0.00027775334,0.0023072527,0.000015171892,0.00003819813],"category_scores_gemma":[0.00043100675,0.0000776118,0.000020619877,0.0002362745,0.00022110384,0.00062609056,0.0010752934,0.00054685224,1.9782163e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096424384,0.00002575406,0.99671894,0.00007940763,0.00003610777,0.000038826867,0.00026787212,0.00093995425,0.000008824027,0.00007906321,0.0004342755,0.0004067538],"study_design_scores_gemma":[0.0010473091,0.00008308098,0.98658115,0.00014420482,0.000011572651,0.004396669,0.00028406217,0.0045311763,0.0000010579123,0.000030655727,0.002798359,0.00009067811],"about_ca_topic_score_codex":0.684986,"about_ca_topic_score_gemma":0.7452017,"teacher_disagreement_score":0.060215704,"about_ca_system_score_codex":0.0027703315,"about_ca_system_score_gemma":0.004045784,"threshold_uncertainty_score":0.9984556},"labels":[],"label_agreement":null},{"id":"W4294242992","doi":"10.23889/ijpds.v7i3.1860","title":"Prenatal Exposure to Intimate Partner Violence and Developmental Health in Children at Kindergarten: Linking Canadian Population-Level Administrative Data.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Intimate Partner and Family Violence","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health; University of Calgary","funders":"","keywords":"Domestic violence; Population; Demography; Cohort; Medicine; Poison control; Cohort study; Vulnerability (computing); Logistic regression; Child development; Neighbourhood (mathematics); Injury prevention; Psychology; Environmental health; Psychiatry; Computer security","score_opus":0.11241084821445797,"score_gpt":0.41837117223442727,"score_spread":0.3059603240199693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294242992","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97934926,0.00018781918,0.0017072834,0.0040559764,0.003071832,0.0014229477,0.009226568,0.00004286083,0.00093547493],"genre_scores_gemma":[0.98787653,0.00009619457,0.0072385897,0.0011119925,0.0001973456,0.000024216339,0.0033769791,0.000009987522,0.000068184396],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.996997,0.00013867873,0.0005262674,0.00065016875,0.0011513063,0.0005365943],"domain_scores_gemma":[0.99869794,0.000080045036,0.00025712044,0.0003134279,0.00022067298,0.00043077787],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0036484348,0.00013418589,0.00015193126,0.00054265093,0.0030189753,0.0004944707,0.0027574734,0.000033650842,0.00011099882],"category_scores_gemma":[0.0006216406,0.0001441572,0.00001843403,0.0005260033,0.00015290816,0.0025586493,0.0013793048,0.00023847366,0.000007449738],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000073787625,0.00005925089,0.93582577,0.000005020541,0.000027709462,0.000010285646,0.0031141571,0.0016263465,0.000017887267,0.012069774,0.0014612928,0.04570871],"study_design_scores_gemma":[0.0003512965,0.000055671917,0.987742,0.00014616894,0.0000040252617,0.00012813183,0.0012641139,0.0045781396,0.000004843629,0.0011208843,0.0043800166,0.00022468477],"about_ca_topic_score_codex":0.10471907,"about_ca_topic_score_gemma":0.11447256,"teacher_disagreement_score":0.051916245,"about_ca_system_score_codex":0.0016758014,"about_ca_system_score_gemma":0.0016831344,"threshold_uncertainty_score":0.998279},"labels":[],"label_agreement":null},{"id":"W4294243049","doi":"10.23889/ijpds.v7i3.1812","title":"Linking Canadian Administrative Data: Income Trajectories, Residential and School Mobility, and Grade 3 Academic Achievement.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health; University of Calgary","funders":"","keywords":"Numeracy; Literacy; Neighbourhood (mathematics); Population; Cohort; Demography; Census; Cohort study; Family income; Medicine; Geography; Gerontology; Psychology; Sociology; Economic growth; Economics; Pedagogy; Mathematics","score_opus":0.16062659871651092,"score_gpt":0.4716104275400952,"score_spread":0.3109838288235843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9480781,0.0005945277,0.0003992274,0.03981696,0.006166331,0.0005945801,0.0041221967,0.000024947825,0.0002031596],"genre_scores_gemma":[0.9966855,0.000281469,0.00083277305,0.0008956313,0.0006246303,0.00000895636,0.0004978158,0.000004962555,0.00016827864],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976885,0.0001266346,0.0003599187,0.00038586187,0.0010962043,0.00034291958],"domain_scores_gemma":[0.9986995,0.0001904659,0.00019458272,0.0002507327,0.00017448326,0.00049024523],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004843932,0.00007416323,0.00009663309,0.00026227545,0.003527028,0.00065796793,0.0021638696,0.00003614904,0.000104674626],"category_scores_gemma":[0.0019061231,0.0000773451,0.000012599682,0.00025224965,0.00029406016,0.0036059094,0.0009313869,0.0003803147,6.603482e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030309178,0.00001624455,0.9588102,0.00001041984,0.000015386615,0.0000076040023,0.0011561504,0.000027881235,0.000010965475,0.035271518,0.0017334103,0.0029099225],"study_design_scores_gemma":[0.00033778432,0.000035101984,0.81282693,0.000033847027,0.0000117519,0.00003965765,0.0033177645,0.0017631303,0.0000016080144,0.007814008,0.17368196,0.00013644928],"about_ca_topic_score_codex":0.1790358,"about_ca_topic_score_gemma":0.2960868,"teacher_disagreement_score":0.17194854,"about_ca_system_score_codex":0.0006045893,"about_ca_system_score_gemma":0.0022308286,"threshold_uncertainty_score":0.99777025},"labels":[],"label_agreement":null},{"id":"W4294243069","doi":"10.23889/ijpds.v7i3.1772","title":"Associations of Congenital Heart Disease with Deprivation Index by Rural-Urban Maternal Residence: A Population-Based Retrospective Cohort Study in Ontario, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Congenital Heart Disease Studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa; Ottawa Hospital; Newborn Screening Ontario","funders":"","keywords":"Residence; Retrospective cohort study; Medicine; Demography; Cohort; Cohort study; Index (typography); Population; Pediatrics; Environmental health; Gerontology; Internal medicine","score_opus":0.02378817399645105,"score_gpt":0.3233771526704775,"score_spread":0.29958897867402645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243069","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99519944,0.000024021492,0.0001171339,0.00079522,0.000543627,0.0010153496,0.0022738853,0.000011919553,0.000019392619],"genre_scores_gemma":[0.997501,5.2735413e-7,0.00020100194,0.00018191017,0.00006054027,0.000075332086,0.0018032176,0.000012837032,0.00016359206],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9960461,0.00006544078,0.0006041177,0.00037834182,0.0026788667,0.00022710126],"domain_scores_gemma":[0.99814415,0.000093483744,0.00035220818,0.00034163578,0.00089283905,0.00017569381],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093010446,0.00013468544,0.00025764655,0.00040857596,0.0005351385,0.00009569605,0.0005479564,0.000015130006,0.00016982813],"category_scores_gemma":[0.0007111649,0.00012985198,0.00003911952,0.0005116588,0.00007056902,0.0008751245,0.00023491925,0.00027284154,3.123164e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006293534,0.00025552823,0.9969394,0.0000028620107,0.000070524875,0.000022121882,0.00008371618,0.0006740641,0.000054099306,0.00003647535,0.0011699466,0.00006190413],"study_design_scores_gemma":[0.0015363412,0.00016966734,0.9916093,0.00003599028,0.0000751305,0.000021687772,0.00024745797,0.0059765074,0.0000060052685,0.00013241197,0.000063211635,0.00012631915],"about_ca_topic_score_codex":0.81573534,"about_ca_topic_score_gemma":0.8977694,"teacher_disagreement_score":0.08203406,"about_ca_system_score_codex":0.00422319,"about_ca_system_score_gemma":0.0028798284,"threshold_uncertainty_score":0.9995994},"labels":[],"label_agreement":null},{"id":"W4294243074","doi":"10.23889/ijpds.v7i3.1948","title":"Supporting health and well-being among infants born to First Nations parents experiencing incarceration: a partnership-based whole-population administrative data study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; First Nations Health and Social Secretariat of Manitoba; Manitoba Health","funders":"","keywords":"Propensity score matching; Confounding; Medicine; Socioeconomic status; Demography; Population; Cohort study; Low birth weight; Birth weight; Pregnancy; Environmental health","score_opus":0.09566913156471003,"score_gpt":0.47043112516542046,"score_spread":0.37476199360071044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243074","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9887253,0.000028073171,0.0025490294,0.0031275493,0.002389445,0.0017218235,0.00033389425,0.00005042129,0.0010744368],"genre_scores_gemma":[0.99394935,0.000041830855,0.0017958189,0.00026502204,0.0007069122,0.000036542264,0.0029013862,0.000014202757,0.0002889313],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99534184,0.0003850823,0.00089250185,0.00075824367,0.002074033,0.0005483013],"domain_scores_gemma":[0.99725467,0.0003798569,0.0006727178,0.0005796064,0.0006146178,0.000498533],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0071843406,0.00015428216,0.00018445583,0.00074193935,0.02655097,0.0010074889,0.0020606255,0.000034851935,0.00007834711],"category_scores_gemma":[0.0008375478,0.00015783527,0.000027458791,0.0009680313,0.00017319541,0.004324202,0.0001379461,0.00023999228,0.0000026601595],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097420234,0.0003797929,0.6085369,0.000017344873,0.000030836374,0.0000074866857,0.3718575,0.002433606,0.0000020956147,0.014620913,0.0006339691,0.0013821395],"study_design_scores_gemma":[0.0016763435,0.0007420549,0.37909275,0.00021042452,0.00003983963,0.000050453473,0.1954411,0.057011325,0.000009556141,0.0012902854,0.36367774,0.00075809774],"about_ca_topic_score_codex":0.045105178,"about_ca_topic_score_gemma":0.5808472,"teacher_disagreement_score":0.53574204,"about_ca_system_score_codex":0.0011085767,"about_ca_system_score_gemma":0.008643889,"threshold_uncertainty_score":0.9969762},"labels":[],"label_agreement":null},{"id":"W4294243087","doi":"10.23889/ijpds.v7i3.1945","title":"Risk of children being taken into care amongst Metis parents experiencing incarceration: A linked administrative data study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Metis; Medicine; Demography; Hazard ratio; Cohort; Socioeconomic status; Mental health; Confounding; Foster care; Pediatrics; Psychiatry; Population; Environmental health; Confidence interval","score_opus":0.09958688515929719,"score_gpt":0.4589747202320553,"score_spread":0.3593878350727581,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243087","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98989165,0.00012297132,0.003636616,0.00016837085,0.00241088,0.00076009677,0.0028432638,0.000020178937,0.00014595554],"genre_scores_gemma":[0.99150413,0.000012387713,0.0023699463,0.00007453317,0.00042327878,0.000073375944,0.005489017,0.000012918392,0.00004039756],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9964999,0.0002749158,0.00085269345,0.0007013824,0.0014184914,0.00025260492],"domain_scores_gemma":[0.9973416,0.00013415946,0.00070001924,0.0010110126,0.0006577033,0.00015554029],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0022764492,0.00014105809,0.00018560812,0.00040742656,0.001565333,0.00022352427,0.0036838565,0.000031446827,0.00036204042],"category_scores_gemma":[0.00075466355,0.00013999097,0.00004193372,0.00047965892,0.000112798334,0.0020239996,0.0010275221,0.0003243107,0.0000035755345],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022788362,0.00028503028,0.91518205,0.00000375528,0.0001496599,0.000007452705,0.06154268,0.00049892714,0.000044580855,0.001003532,0.00092729065,0.020127133],"study_design_scores_gemma":[0.0013951465,0.00043655463,0.94175047,0.000015565565,0.000057827805,0.000085830754,0.048421185,0.0063996133,0.000024360661,0.0003853993,0.0008574489,0.00017058609],"about_ca_topic_score_codex":0.004935198,"about_ca_topic_score_gemma":0.0026781813,"teacher_disagreement_score":0.026568405,"about_ca_system_score_codex":0.0002728436,"about_ca_system_score_gemma":0.00039017372,"threshold_uncertainty_score":0.9997345},"labels":[],"label_agreement":null},{"id":"W4294243101","doi":"10.23889/ijpds.v7i3.1951","title":"Estimating Disease Heritability from Electronic Healthcare Records: A Proof-of-Concept Study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"CancerCare Manitoba; University of Manitoba","funders":"","keywords":"Heritability; Interquartile range; Demography; Medicine; Disease; Population; Health care; Family medicine; Environmental health; Biology; Genetics; Internal medicine","score_opus":0.09618061089280677,"score_gpt":0.43563226584691533,"score_spread":0.33945165495410856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243101","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98101115,0.0002515297,0.009432322,0.00425205,0.0025196995,0.0011652762,0.0012855105,0.00003358274,0.000048868416],"genre_scores_gemma":[0.9949617,0.0000018282273,0.0032014088,0.0001425012,0.00034129716,0.00004814164,0.0012383703,0.000009538015,0.00005525728],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99737,0.00006733587,0.00049021817,0.00043579278,0.0014036787,0.0002329517],"domain_scores_gemma":[0.99851143,0.000071497256,0.00036566897,0.00053013023,0.0003602701,0.00016098437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012639702,0.00009385034,0.00015090014,0.00019829578,0.00044449038,0.00012645926,0.0011997898,0.000007886269,0.00033767868],"category_scores_gemma":[0.0008937381,0.00009096934,0.00005787387,0.00025130948,0.00009970183,0.0010867141,0.0006700249,0.00020793319,5.469914e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027637782,0.003398122,0.7665426,0.00013354048,0.00042542472,0.00010927218,0.0016404672,0.03514128,0.00011865028,0.0073720897,0.0026746304,0.17968012],"study_design_scores_gemma":[0.0034547874,0.00096062117,0.5668936,0.00013972679,0.00020260777,0.000042693973,0.0027548005,0.3970859,0.000025308826,0.024249014,0.0039275587,0.00026336504],"about_ca_topic_score_codex":0.0009860035,"about_ca_topic_score_gemma":0.00012181542,"teacher_disagreement_score":0.36194465,"about_ca_system_score_codex":0.00078448094,"about_ca_system_score_gemma":0.0011409166,"threshold_uncertainty_score":0.3709622},"labels":[],"label_agreement":null},{"id":"W4294243109","doi":"10.23889/ijpds.v7i1.1690","title":"Laying the Foundation for Real-World Evidence Studies of Psoriatic Disease in Newfoundland and Labrador","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Newfoundland and Labrador Centre for Applied Health Research; Memorial University of Newfoundland","funders":"","keywords":"General partnership; Psychological intervention; Foundation (evidence); Business; Disease; Medicine; Environmental planning; Knowledge management; Geography; Nursing; Computer science; Finance","score_opus":0.5278289798605712,"score_gpt":0.6041311672428868,"score_spread":0.07630218738231564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243109","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.967233,0.0002213875,0.0054271226,0.02421605,0.001904722,0.0008294088,0.00015531726,0.000006704075,0.000006285129],"genre_scores_gemma":[0.9936798,0.00028577624,0.0049840943,0.0004529508,0.00027027493,0.000043379277,0.00021473851,0.000005526304,0.00006341296],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99813765,0.00006361984,0.00071190466,0.00022174754,0.00075870147,0.000106365515],"domain_scores_gemma":[0.99641913,0.0021378063,0.00055226986,0.00022484415,0.000607383,0.000058536913],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0050957995,0.00005667286,0.00011751062,0.00026819197,0.00039620334,0.00009239698,0.00046319905,0.000005767682,0.000024267476],"category_scores_gemma":[0.016898297,0.00004314084,0.000029228251,0.00031522827,0.000109888446,0.0016279375,0.00032068978,0.00011278159,2.6119022e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013528102,0.00009330921,0.93020666,0.00005633818,0.00005966456,0.000003670476,0.0004242877,0.0022734518,0.00045403314,0.0060233297,0.0007105212,0.058341924],"study_design_scores_gemma":[0.001682193,0.00016447519,0.889,0.00015751057,0.00011750289,0.000030199853,0.0012024409,0.094911866,0.0000042958522,0.008493069,0.0041626347,0.00007379377],"about_ca_topic_score_codex":0.0015307331,"about_ca_topic_score_gemma":0.0017144014,"teacher_disagreement_score":0.09263841,"about_ca_system_score_codex":0.00041066232,"about_ca_system_score_gemma":0.0003199913,"threshold_uncertainty_score":0.9913828},"labels":[],"label_agreement":null},{"id":"W4294243125","doi":"10.23889/ijpds.v7i3.1974","title":"Changes in health and welfare after workers’ compensation benefits cease.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Receipt; Workers' compensation; Payment; Welfare; Social security; Business; Disability benefits; Compensation (psychology); Social work; Social Welfare; Demographic economics; Medicine; Actuarial science; Labour economics; Economics; Finance; Economic growth; Accounting; Psychology; Political science","score_opus":0.1433948902128118,"score_gpt":0.46463721354483495,"score_spread":0.3212423233320232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243125","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89416766,0.00047677633,0.00018059347,0.09944324,0.004210476,0.00060296437,0.00078096864,0.000024462932,0.00011286335],"genre_scores_gemma":[0.9968474,0.00012287797,0.0004028513,0.0016415823,0.0002549499,0.00008292234,0.00044593523,0.0000074144873,0.00019407962],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99824154,0.00013106242,0.0004026912,0.00027041222,0.00068504666,0.0002692565],"domain_scores_gemma":[0.9990966,0.000100145815,0.00032848198,0.00016275757,0.00020728394,0.00010477593],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002178581,0.00007572373,0.00011221327,0.00037963394,0.0021707923,0.00005443636,0.0006067918,0.000016836662,0.00026343603],"category_scores_gemma":[0.0002784089,0.00007061318,0.000013893341,0.00025286697,0.000052782972,0.00076569454,0.0008262993,0.00025855732,0.000002083856],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012719394,0.00002506268,0.9773283,0.000013582669,0.000008096522,0.000002083738,0.0013064488,0.00023580683,0.0000038008181,0.006545649,0.0015641997,0.012839771],"study_design_scores_gemma":[0.00065371935,0.00007397812,0.91506624,0.000100501784,0.0000025731451,0.000010827764,0.0037347863,0.0023140025,2.9719504e-7,0.0010073881,0.07694794,0.0000877193],"about_ca_topic_score_codex":0.0007247325,"about_ca_topic_score_gemma":0.0022464318,"teacher_disagreement_score":0.10267974,"about_ca_system_score_codex":0.00040022077,"about_ca_system_score_gemma":0.00016894433,"threshold_uncertainty_score":0.9991282},"labels":[],"label_agreement":null},{"id":"W4294243143","doi":"10.23889/ijpds.v7i3.1954","title":"The effect of opioid analgesics, benzodiazepines, gabapentinoids, and opioid agonist treatment on mortality risk among opioid-dependent people.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Medicine; Opioid; Analgesic; Anesthesia; Incidence (geometry); Cohort; Internal medicine; Pharmacoepidemiology; Concomitant; Medical prescription; Pharmacology","score_opus":0.08533858784853963,"score_gpt":0.43216772217390037,"score_spread":0.3468291343253607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9950034,0.0002374521,0.00016789371,0.0006651874,0.0023105508,0.0006086585,0.00090104184,0.0000101984515,0.00009561848],"genre_scores_gemma":[0.9981619,0.0006966552,0.00013070264,0.00009461873,0.00020988002,0.000027188238,0.00053875946,0.000008741002,0.00013152816],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99748576,0.00014438175,0.00047442652,0.00033851145,0.0013444389,0.00021249813],"domain_scores_gemma":[0.9980243,0.00064597366,0.000597172,0.00039455885,0.00016864148,0.00016938247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002294171,0.00013698086,0.00020683926,0.00015744402,0.001124829,0.00021371391,0.00075440423,0.000019397712,0.00007139497],"category_scores_gemma":[0.00103583,0.000087848464,0.00009060251,0.0001856282,0.0001694935,0.0006878729,0.00039215738,0.00026775227,0.0000016508185],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006356116,0.00011315305,0.9789202,0.000015237558,0.00012436906,0.000007813344,0.00008354702,0.00032287027,0.00018813854,0.0005204393,0.00020813652,0.01886046],"study_design_scores_gemma":[0.0018523012,0.0011725824,0.9621096,0.00002607646,0.0002265989,0.000071618284,0.00008222766,0.022973731,0.0006277354,0.00034261553,0.010413404,0.00010146157],"about_ca_topic_score_codex":0.0009582233,"about_ca_topic_score_gemma":0.0001951284,"teacher_disagreement_score":0.02265086,"about_ca_system_score_codex":0.00026991023,"about_ca_system_score_gemma":0.00013535039,"threshold_uncertainty_score":0.86513895},"labels":[],"label_agreement":null},{"id":"W4294243159","doi":"10.23889/ijpds.v7i3.1852","title":"Our Children, Our Future: The Health and Well-being of First Nations Children in Manitoba, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"First Nations Health and Social Secretariat of Manitoba; University of Manitoba","funders":"","keywords":"Indigenous; Population; Mental health; Medicine; Breastfeeding; Economic Justice; Demography; Political science; Pediatrics; Psychiatry; Environmental health; Sociology; Law","score_opus":0.02608261436421898,"score_gpt":0.34512147129891374,"score_spread":0.31903885693469475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.927417,0.0002706862,0.00013568875,0.063402876,0.006770135,0.0008796749,0.00035270074,0.000010858101,0.0007604183],"genre_scores_gemma":[0.9965819,0.0012589858,0.00031284508,0.0002623042,0.0010992239,0.0000039256893,0.00029652703,0.0000053437316,0.0001789204],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977121,0.00014947169,0.00041069905,0.00023207026,0.0012134925,0.0002821705],"domain_scores_gemma":[0.99890584,0.00006429795,0.00041405304,0.00019524542,0.00028312838,0.0001374079],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002979526,0.000069212016,0.00009386083,0.00033515875,0.012099061,0.00015405803,0.0015880666,0.000018122353,0.000009774052],"category_scores_gemma":[0.00009255479,0.000055814045,0.000020267447,0.0005723964,0.000054936736,0.00081615685,0.00003660025,0.0002035396,3.7802863e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032216085,0.0001392534,0.6918352,0.000008362837,0.000031699426,0.0000012119881,0.053822264,0.0007382777,4.0064788e-7,0.24633792,0.005204834,0.001848333],"study_design_scores_gemma":[0.00046687308,0.00005955312,0.7105564,0.000038967624,0.000007840773,0.000111894085,0.047823504,0.00071033114,0.0000023873429,0.0025132548,0.23753689,0.00017211518],"about_ca_topic_score_codex":0.90026766,"about_ca_topic_score_gemma":0.9978115,"teacher_disagreement_score":0.24382466,"about_ca_system_score_codex":0.0009228522,"about_ca_system_score_gemma":0.012932819,"threshold_uncertainty_score":0.9926629},"labels":[],"label_agreement":null},{"id":"W4294243177","doi":"10.23889/ijpds.v7i3.1933","title":"Methamphetamine Use in Manitoba: An Evidence-to-Action (E2A) approach to a linked administrative data study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health","funders":"","keywords":"Action (physics); Computer science","score_opus":0.7201607798475115,"score_gpt":0.5493799291319195,"score_spread":0.17078085071559201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243177","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9139045,0.000005378576,0.08104403,0.0007701539,0.0017799975,0.0014411204,0.0009910128,0.000036765512,0.000027038153],"genre_scores_gemma":[0.8875682,0.0000022604781,0.110146984,0.0001533705,0.00030266668,0.00008327598,0.0016516589,0.000017321034,0.00007429658],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9960558,0.00024091091,0.0008154633,0.0008013407,0.0018242177,0.00026226713],"domain_scores_gemma":[0.99718523,0.0004152276,0.00044952717,0.0011712002,0.0005613976,0.00021739794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054922327,0.00016284136,0.00020544893,0.00085363496,0.00065548107,0.0006263489,0.003370673,0.00002710278,0.00004900068],"category_scores_gemma":[0.005760166,0.00016240148,0.000029116367,0.0009928964,0.00003378039,0.0068870676,0.001407072,0.00026700718,0.0000041307644],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031649047,0.008334291,0.69663894,0.00006639401,0.00026247028,0.00007561334,0.011637255,0.110346355,0.0034196253,0.0512012,0.012803899,0.102049075],"study_design_scores_gemma":[0.0009055415,0.0005233999,0.596044,0.00005698634,0.00004519404,0.00017656003,0.003282062,0.389444,0.000014513543,0.00557318,0.003581906,0.00035264317],"about_ca_topic_score_codex":0.0010837737,"about_ca_topic_score_gemma":0.004139682,"teacher_disagreement_score":0.27909765,"about_ca_system_score_codex":0.00071322743,"about_ca_system_score_gemma":0.00022777931,"threshold_uncertainty_score":0.68958724},"labels":[],"label_agreement":null},{"id":"W4294243178","doi":"10.23889/ijpds.v7i3.1931","title":"Predicting Surgical Service Demands: A Modeling challenge using Administrative Data.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Medical diagnosis; Service (business); Population; Health care; Matching (statistics); Diagnosis code; Resource (disambiguation); Computer science; Medical emergency; Actuarial science; Operations management; Operations research; Medicine; Business; Engineering","score_opus":0.5214063809012668,"score_gpt":0.46304847679294653,"score_spread":0.05835790410832026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243178","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.688439,0.0010347026,0.23283046,0.043627318,0.011720134,0.0010321024,0.018153219,0.00009353359,0.003069511],"genre_scores_gemma":[0.993569,0.000059492224,0.004592066,0.00040773637,0.0005532743,0.000009651938,0.0007661406,0.000009338022,0.000033279644],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998279,0.000024223149,0.0006540127,0.0005072186,0.0002878822,0.00024766615],"domain_scores_gemma":[0.99873906,0.000050649593,0.0004469266,0.00050098787,0.00015384985,0.00010854036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035845838,0.0000813173,0.00013468612,0.00033841652,0.00095350674,0.0002731921,0.0026701046,0.000019331805,0.00010323476],"category_scores_gemma":[0.00036261653,0.00009544004,0.000026823736,0.00029928968,0.0000256528,0.0025029883,0.0016760319,0.00020064003,0.00000597191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002071984,0.00033421823,0.02787541,0.000048569702,0.00018297268,0.00006073599,0.0016948954,0.25198245,0.000010669686,0.7085051,0.0005398487,0.008557944],"study_design_scores_gemma":[0.00033426622,0.000031680618,0.00042115935,0.000011983353,0.0000040157897,0.00009574935,0.00029170976,0.9459251,3.6296214e-7,0.010453265,0.042331014,0.0000996676],"about_ca_topic_score_codex":0.0028720095,"about_ca_topic_score_gemma":0.00030580655,"teacher_disagreement_score":0.6980518,"about_ca_system_score_codex":0.00032048198,"about_ca_system_score_gemma":0.00014972307,"threshold_uncertainty_score":0.73336995},"labels":[],"label_agreement":null},{"id":"W4294243181","doi":"10.23889/ijpds.v7i3.1939","title":"Considerations and Consequences when using First Nations Identifiers in Administrative Data Research.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; First Nations Health and Social Secretariat of Manitoba; Manitoba Health","funders":"","keywords":"Indigenous; Population; Identifier; General partnership; Geography; Unique identifier; Cohort; Medicine; Demography; Political science; Environmental health; Computer science; Sociology","score_opus":0.6774907370340509,"score_gpt":0.6137504215913975,"score_spread":0.06374031544265346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243181","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8764053,0.00072924444,0.004820658,0.07179378,0.019488543,0.004364547,0.018563366,0.000057942376,0.003776649],"genre_scores_gemma":[0.9937196,0.00009873904,0.00477698,0.00031093904,0.00020224423,0.00006181701,0.0006735327,0.000006389703,0.00014976726],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.997379,0.0003345558,0.0005602409,0.00043136164,0.0008117744,0.00048306998],"domain_scores_gemma":[0.99639505,0.001811518,0.0003073739,0.00041300786,0.0009859488,0.00008712437],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008334791,0.00006949411,0.00011661092,0.0007381672,0.021885516,0.00017179822,0.0014948284,0.000030890224,0.00046709564],"category_scores_gemma":[0.007062179,0.000069336056,0.000011354486,0.00038366832,0.00047625383,0.0018889705,0.002865062,0.00053251267,0.0000032295413],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027733095,0.00036477565,0.54295456,0.00006705401,0.00019699709,0.00016215799,0.06704364,0.004671615,0.0005875867,0.3325372,0.0503045,0.00083255005],"study_design_scores_gemma":[0.0037085619,0.0004190032,0.11153156,0.00029166578,0.000063342515,0.0010079249,0.25943357,0.22599977,0.000014084538,0.14787725,0.24894153,0.0007117529],"about_ca_topic_score_codex":0.0065799146,"about_ca_topic_score_gemma":0.16918518,"teacher_disagreement_score":0.43142304,"about_ca_system_score_codex":0.0008566469,"about_ca_system_score_gemma":0.0020549216,"threshold_uncertainty_score":0.99469066},"labels":[],"label_agreement":null},{"id":"W4294243190","doi":"10.23889/ijpds.v7i3.1815","title":"A Feasibility Study for CODE-MI: High-Sensitivity Cardiac Troponin - Optimizing the Diagnosis of Acute Myocardial Infarction/Injury in Women.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Acute Myocardial Infarction Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; University of British Columbia; Centre for Advancing Health Outcomes","funders":"","keywords":"Medicine; Emergency department; Myocardial infarction; Cohort; Chest pain; Acute coronary syndrome; Troponin; Emergency medicine; Revascularization; Internal medicine; Randomized controlled trial; Conventional PCI; Cardiology","score_opus":0.07843222045751017,"score_gpt":0.42444275926741426,"score_spread":0.34601053880990407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9791751,0.000017182994,0.002549012,0.008697776,0.0030957523,0.0019750742,0.0044567944,0.0000169629,0.000016332895],"genre_scores_gemma":[0.9960418,0.00005128802,0.0019682995,0.00059996295,0.00043246738,0.00050997495,0.00034151613,0.000016252572,0.000038473543],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99611735,0.00034546177,0.00067272625,0.000510178,0.0019908035,0.00036350556],"domain_scores_gemma":[0.9973954,0.000474456,0.00036919033,0.0006533415,0.00096514565,0.00014244334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009200426,0.0001324617,0.00033842464,0.0005973662,0.0008215322,0.00016000638,0.0010316618,0.000031462838,0.00007019579],"category_scores_gemma":[0.0017720206,0.00011099661,0.00016310961,0.00077821285,0.00024606957,0.0010442392,0.00091539946,0.00044364174,9.794328e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010017553,0.0018378558,0.9267394,0.000018671493,0.001769231,0.000038558523,0.0020157879,0.013610639,0.0075726733,0.0014037922,0.016919432,0.018056408],"study_design_scores_gemma":[0.004080049,0.0014302764,0.9555394,0.000025962003,0.0002099288,0.00015801085,0.0028324034,0.019999862,0.00040387726,0.0008986355,0.014191114,0.00023048172],"about_ca_topic_score_codex":0.00075875875,"about_ca_topic_score_gemma":0.000020390014,"teacher_disagreement_score":0.0288,"about_ca_system_score_codex":0.0014274783,"about_ca_system_score_gemma":0.0005387244,"threshold_uncertainty_score":0.6318645},"labels":[],"label_agreement":null},{"id":"W4294243193","doi":"10.23889/ijpds.v7i3.1795","title":"Potentially non-beneficial interventions in the last 100 days of life of patients with cancer: A population-based retrospective cohort study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Childhood Cancer Survivors' Quality of Life","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa; Bruyère; McMaster University; Ottawa Hospital","funders":"","keywords":"Retrospective cohort study; Medicine; Cohort; Cancer; Psychological intervention; Population; Cohort study; Oncology; Internal medicine; Intensive care medicine; Environmental health; Psychiatry","score_opus":0.0463861446030322,"score_gpt":0.3797630712538961,"score_spread":0.3333769266508639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243193","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.992907,0.00001825793,0.0022185463,0.0011084285,0.0010538966,0.0010936606,0.0015710274,0.000006402783,0.000022779577],"genre_scores_gemma":[0.9976876,0.0000029361763,0.00076848484,0.00021477036,0.0001554828,0.000056860128,0.0010947252,0.000011295644,0.000007894906],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9956516,0.00012337582,0.0009296755,0.00034740052,0.0027885472,0.00015942543],"domain_scores_gemma":[0.9973571,0.00011689649,0.0010017735,0.0004495095,0.001004346,0.00007042875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002873164,0.000111693764,0.00030219663,0.000557176,0.0003238483,0.000062609135,0.0013237383,0.0000179315,0.00016586726],"category_scores_gemma":[0.0008653946,0.00008811104,0.000104699684,0.0007691416,0.00009735069,0.0006020163,0.00024386219,0.0002494657,2.3519429e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005516158,0.0010975521,0.98921734,0.000022392323,0.00008766225,0.000001589041,0.0004876683,0.007729531,0.000013326156,0.00016449089,0.00014602867,0.00048077287],"study_design_scores_gemma":[0.0025444655,0.0006221943,0.99202436,0.000140418,0.00008119854,0.0000042401384,0.00063297665,0.003701506,0.0000050229537,0.00010291122,0.000056141573,0.00008454424],"about_ca_topic_score_codex":0.0076803835,"about_ca_topic_score_gemma":0.005501074,"teacher_disagreement_score":0.0047805496,"about_ca_system_score_codex":0.0004622068,"about_ca_system_score_gemma":0.0006267538,"threshold_uncertainty_score":0.99892753},"labels":[],"label_agreement":null},{"id":"W4294243194","doi":"10.23889/ijpds.v7i3.1879","title":"Engaging im/migrant communities in cross-sectoral health and immigration data linkage research.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"SickKids Foundation; Simon Fraser University; University of British Columbia; Hospital for Sick Children; Dalhousie University","funders":"","keywords":"Immigration; Linkage (software); Political science; Data science; Computer science; Biology; Genetics","score_opus":0.36086443610178404,"score_gpt":0.556281129751645,"score_spread":0.19541669364986097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243194","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98574317,0.0009891591,0.0024973126,0.004749126,0.0033034196,0.0004260784,0.002198049,0.000022751115,0.00007092186],"genre_scores_gemma":[0.9914808,0.00014379763,0.0012876226,0.00059892866,0.00031905083,0.000029973027,0.006013513,0.000011280104,0.000114999246],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966232,0.0006083469,0.00067666784,0.00044512187,0.0012026718,0.00044397824],"domain_scores_gemma":[0.997872,0.00038213003,0.0003111771,0.000883699,0.00035089444,0.00020007516],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.014378087,0.000094634546,0.00013096369,0.0008863874,0.002638225,0.0005409385,0.003027778,0.000027578226,0.00024766085],"category_scores_gemma":[0.00047918488,0.00009664647,0.000017084616,0.0005275696,0.00025579592,0.0024443874,0.0011666312,0.00076176244,0.000004586185],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005476511,0.00032384004,0.8460644,0.000032851858,0.00003350272,0.000019109242,0.0458721,0.000693685,0.00006387565,0.026719846,0.016246833,0.06338233],"study_design_scores_gemma":[0.0020097897,0.0003281076,0.7516936,0.00007023872,0.0000037501618,0.00041190608,0.029344492,0.10160018,0.0000021718122,0.0045213983,0.10977994,0.00023442111],"about_ca_topic_score_codex":0.019375194,"about_ca_topic_score_gemma":0.013058255,"teacher_disagreement_score":0.10090649,"about_ca_system_score_codex":0.0003388596,"about_ca_system_score_gemma":0.00051536754,"threshold_uncertainty_score":0.9986602},"labels":[],"label_agreement":null},{"id":"W4294243217","doi":"10.23889/ijpds.v7i3.1927","title":"Birth outcomes among Métis women and infants in Manitoba, Canada: A linked administrative data study using health system and justice system data.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Prenatal Substance Exposure Effects","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"","keywords":"Medicine; Demography; Socioeconomic status; Cohort; Birth weight; Pregnancy; Confounding; Population; Environmental health","score_opus":0.13155093897076967,"score_gpt":0.4008555966017896,"score_spread":0.26930465763101996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243217","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99118376,0.00016931038,0.0006095913,0.00029824208,0.0018726259,0.0009659352,0.0048765475,0.000018515653,0.0000054820657],"genre_scores_gemma":[0.99730766,0.000006950312,0.0013595452,0.00010626586,0.00015218084,0.000018941906,0.00102668,0.000012054467,0.0000097286365],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966817,0.0001745159,0.0006455395,0.0006958051,0.0014725992,0.00032987408],"domain_scores_gemma":[0.99788374,0.00021296307,0.0005349176,0.00093641353,0.00017129898,0.00026068388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045768046,0.00014342985,0.00032152326,0.00032980848,0.00067387306,0.00023487893,0.0019589406,0.000017698167,0.0000033659949],"category_scores_gemma":[0.00092618074,0.00012983009,0.000007128177,0.0003582677,0.000082365565,0.0023742865,0.0025657057,0.00028918573,1.3444398e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022305669,0.000086417574,0.9957786,0.00017393578,0.000084629115,0.00026855533,0.00070811313,0.00017346193,0.00003553216,0.00019655557,0.00018121231,0.0020899256],"study_design_scores_gemma":[0.0015092255,0.00016840242,0.8073033,0.00019915542,0.00003662671,0.0008070019,0.01404549,0.17566413,6.8312704e-7,0.0000045773554,0.00015393179,0.00010749787],"about_ca_topic_score_codex":0.15118858,"about_ca_topic_score_gemma":0.32444695,"teacher_disagreement_score":0.18847533,"about_ca_system_score_codex":0.0024586422,"about_ca_system_score_gemma":0.0015882489,"threshold_uncertainty_score":0.8544637},"labels":[],"label_agreement":null},{"id":"W4294243219","doi":"10.23889/ijpds.v7i3.1941","title":"Outcomes of children involved with child protection in Manitoba, Canada: a demonstration project for working in partnership across government, community organizations, and academia.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child Abuse and Trauma","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Assembly of Manitoba Chiefs; Manitoba Health; First Nations Health and Social Secretariat of Manitoba; Government of Manitoba; University of Manitoba","funders":"","keywords":"General partnership; Government (linguistics); Framing (construction); Mental health; Agency (philosophy); Public relations; Child protection; Political science; Psychology; Medicine; Sociology; Nursing; Psychiatry; Geography","score_opus":0.10859538203781458,"score_gpt":0.3738945567709583,"score_spread":0.2652991747331437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243219","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966994,0.000024814566,0.0010233046,0.0006992018,0.000337182,0.00078846706,0.00038239273,0.0000058516366,0.000039421895],"genre_scores_gemma":[0.99901,0.000004424829,0.00037792383,0.00012453839,0.000060261053,0.00007383465,0.00032743378,0.000008442693,0.000013129908],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99854606,0.00010385787,0.00038088363,0.00021578421,0.0005800247,0.00017338354],"domain_scores_gemma":[0.99922556,0.00010568115,0.00034317776,0.0001867246,0.00010898209,0.000029895842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015553285,0.00008204421,0.00011869104,0.00015187486,0.00060162705,0.00007516401,0.0006984993,0.000035324432,0.000009547135],"category_scores_gemma":[0.0003203684,0.00007633097,0.000011917218,0.0004990218,0.00006283425,0.0005926145,0.00018157286,0.0004879672,6.535477e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018863386,0.00010331981,0.99277526,0.0000028751838,0.000028537494,9.892448e-7,0.0008986657,0.00063472707,0.000021858323,0.0009524014,0.000080234444,0.0043124785],"study_design_scores_gemma":[0.0014974856,0.00006782746,0.99270624,0.00003797837,0.0000072633247,0.0000683745,0.0034899684,0.0015625663,0.00003354037,0.00015748874,0.0002866359,0.00008465091],"about_ca_topic_score_codex":0.13333027,"about_ca_topic_score_gemma":0.6616871,"teacher_disagreement_score":0.5283568,"about_ca_system_score_codex":0.00047519102,"about_ca_system_score_gemma":0.00022621274,"threshold_uncertainty_score":0.87244093},"labels":[],"label_agreement":null},{"id":"W4294243232","doi":"10.23889/ijpds.v7i3.1814","title":"Defying Expectations: Can We Identify Neighbourhoods with “Other Than Expected” Developmental Outcomes?","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; McMaster University","funders":"","keywords":"Neighbourhood (mathematics); Contingency table; Quartile; Vulnerability (computing); Demography; Descriptive statistics; Psychology; Co-occurrence; Socioeconomic status; Geography; Developmental psychology; Statistics; Confidence interval; Sociology; Mathematics; Population; Computer science","score_opus":0.08329843350722815,"score_gpt":0.420424208729687,"score_spread":0.33712577522245885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95537484,0.00012312568,0.010379015,0.021322913,0.008599428,0.0007480352,0.0004063535,0.00013091223,0.0029154036],"genre_scores_gemma":[0.97872204,0.000019532557,0.01896034,0.0005895978,0.00031342614,0.00005161733,0.00021334755,0.000014718702,0.0011153875],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99673647,0.00009986795,0.00040049184,0.00039751126,0.002028988,0.0003366975],"domain_scores_gemma":[0.9986689,0.00011537538,0.0003525534,0.00021312016,0.00044985712,0.00020021453],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0015178262,0.00011907072,0.00010960699,0.00048245632,0.0035190198,0.0008634209,0.0021523952,0.000021403548,0.0007403192],"category_scores_gemma":[0.0005888775,0.00010925143,0.000043012933,0.00065886433,0.00016801775,0.0020529877,0.00034812384,0.00018894237,0.000012086528],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055545228,0.00020017728,0.8922989,0.0000022951108,0.00011903847,0.0000078836665,0.057411727,0.0006241619,0.00009832771,0.030438872,0.003052488,0.015690623],"study_design_scores_gemma":[0.001226588,0.00006265038,0.7887562,0.000054154327,0.000022900085,0.0001601954,0.11399577,0.00042978427,0.000039793063,0.0076156477,0.08708889,0.00054741005],"about_ca_topic_score_codex":0.0015033256,"about_ca_topic_score_gemma":0.0026568472,"teacher_disagreement_score":0.10354264,"about_ca_system_score_codex":0.0010715326,"about_ca_system_score_gemma":0.0022184986,"threshold_uncertainty_score":0.99777824},"labels":[],"label_agreement":null},{"id":"W4294243248","doi":"10.23889/ijpds.v7i3.1973","title":"Impacts of past occupational injury and long-duration compensated work disability on future hospital admissions.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Workers' compensation; Duration (music); Emergency medicine; Occupational safety and health; Compensation (psychology); Demography; Psychology","score_opus":0.04874185498813805,"score_gpt":0.3998339300922542,"score_spread":0.35109207510411616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243248","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9910052,0.000059694838,0.0002029769,0.00493561,0.002864497,0.00023046682,0.0006575856,0.000012460114,0.00003151285],"genre_scores_gemma":[0.99748844,0.000040783678,0.0007456469,0.00014664888,0.00052835135,0.000007698366,0.0010200678,0.000005671677,0.00001669247],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981208,0.000029472181,0.00040765986,0.00026556602,0.0010459822,0.00013051678],"domain_scores_gemma":[0.9988084,0.00006619067,0.00026756577,0.00022332899,0.00048510017,0.00014941684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067257823,0.000089337285,0.00012962018,0.00016380679,0.0005463329,0.000047724938,0.00039449436,0.000019534593,0.00015459531],"category_scores_gemma":[0.00085255184,0.000073674135,0.000046607118,0.0003301032,0.00013696938,0.0006241054,0.00025957928,0.00016980982,7.619667e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009178845,0.00023235213,0.9750564,0.000007071688,0.00004321025,0.0000030016,0.00019209554,0.000096725074,0.00037978738,0.00077607966,0.0038561095,0.018439261],"study_design_scores_gemma":[0.0005212649,0.00033351622,0.9951686,0.000042944695,0.00002027539,0.000044018587,0.00024496985,0.0006510359,0.00004869634,0.00016769432,0.0026813953,0.000075535514],"about_ca_topic_score_codex":0.000044278335,"about_ca_topic_score_gemma":0.000019107232,"teacher_disagreement_score":0.020112231,"about_ca_system_score_codex":0.00022401875,"about_ca_system_score_gemma":0.00016733083,"threshold_uncertainty_score":0.42020062},"labels":[],"label_agreement":null},{"id":"W4294243277","doi":"10.23889/ijpds.v7i3.1847","title":"Care trajectory in homes care users across mortality-risk profiles: an observational study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ottawa Hospital; University of Ottawa; Bruyère","funders":"","keywords":"Medicine; Palliative care; Emergency department; Cohort; Observational study; Health care; Retrospective cohort study; Advance care planning; Emergency medicine; Population; Cohort study; Risk assessment; Acute care; Demography; Gerontology; Family medicine; Internal medicine; Environmental health; Nursing","score_opus":0.31658729019580734,"score_gpt":0.5559924408488707,"score_spread":0.23940515065306334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243277","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98674333,0.00015370171,0.0002039977,0.00023016054,0.0079954155,0.00089299114,0.0037014536,0.000035686026,0.000043271557],"genre_scores_gemma":[0.9947026,0.00001628772,0.00071261515,0.00012003226,0.00064891635,0.00013624023,0.0035695024,0.00001689313,0.000076917866],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9962315,0.00038800933,0.0007357832,0.00054010487,0.0016830225,0.00042155894],"domain_scores_gemma":[0.9976219,0.00018377394,0.00054376444,0.00051156076,0.0010070441,0.00013197237],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002704984,0.00013460316,0.0001844136,0.00040310613,0.0031795315,0.00015162674,0.0021267817,0.00004339677,0.00018322571],"category_scores_gemma":[0.00059543573,0.00013212136,0.00005554036,0.00061124057,0.00008110002,0.002202718,0.00060992857,0.0006420731,0.0000036987249],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000109521316,0.000111483205,0.95223814,0.000014382369,0.000018092094,0.000008140418,0.038467277,0.0036756822,0.000028262195,0.00013399837,0.0006880141,0.0045070183],"study_design_scores_gemma":[0.00095943734,0.00014377697,0.7543231,0.000021254773,0.000014311276,0.000005888939,0.23982519,0.001219855,0.0000016479373,0.0001637304,0.0032023978,0.000119402284],"about_ca_topic_score_codex":0.0036447383,"about_ca_topic_score_gemma":0.009142859,"teacher_disagreement_score":0.20135792,"about_ca_system_score_codex":0.0013837011,"about_ca_system_score_gemma":0.0010019777,"threshold_uncertainty_score":0.9981182},"labels":[],"label_agreement":null},{"id":"W4294243279","doi":"10.23889/ijpds.v7i3.1952","title":"Prediction of Asthma Risk Using Family Health Histories identified from Population-based Electronic Healthcare Records.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Asthma and respiratory diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"CancerCare Manitoba; University of Manitoba","funders":"","keywords":"Asthma; Medicine; Offspring; Interquartile range; Cohort; Population; Family history; Receiver operating characteristic; Pediatrics; Demography; Internal medicine; Environmental health; Pregnancy","score_opus":0.07955503268302701,"score_gpt":0.38090070844129287,"score_spread":0.3013456757582659,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243279","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9720691,0.0008137933,0.016015727,0.0010692688,0.0038614704,0.00035095084,0.0057846247,0.000030034902,0.0000050585063],"genre_scores_gemma":[0.9922354,0.000035651105,0.0027718516,0.00044264254,0.00043062144,0.000009091898,0.004030349,0.000014314954,0.000030077776],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99708945,0.00012793508,0.0006968544,0.00037796606,0.001461983,0.00024583592],"domain_scores_gemma":[0.99787813,0.00007257879,0.0009587956,0.0003671224,0.0005490131,0.00017437123],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013431389,0.000105350264,0.00020397571,0.00046995727,0.0010120173,0.000071478826,0.0006530979,0.000025757645,0.00007882187],"category_scores_gemma":[0.00048527963,0.00010337567,0.000089542606,0.0003750001,0.00007009216,0.00084561366,0.0001514711,0.00026806194,5.4368047e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007641185,0.00021722085,0.95121765,0.000028362265,0.000059011276,0.000005438847,0.00015602265,0.011746273,0.0015995669,0.00062731863,0.0012159668,0.03236304],"study_design_scores_gemma":[0.0011493731,0.000397808,0.8798557,0.000078579134,0.000037276634,0.000039134193,0.00032914482,0.10534834,0.00003838296,0.001057462,0.011568868,0.000099961326],"about_ca_topic_score_codex":0.0066533517,"about_ca_topic_score_gemma":0.00024964366,"teacher_disagreement_score":0.09360207,"about_ca_system_score_codex":0.0016857482,"about_ca_system_score_gemma":0.0019653866,"threshold_uncertainty_score":0.99996144},"labels":[],"label_agreement":null},{"id":"W4294243295","doi":"10.23889/ijpds.v7i3.1871","title":"An analysis of Covid-19 deaths and equality in Northern Ireland.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Economic and Social Research Council","keywords":"Residence; Census; Pandemic; Coronavirus disease 2019 (COVID-19); Demography; Public health; Geography; Medicine; Population; Sociology; Nursing","score_opus":0.14219958038223154,"score_gpt":0.510881573626003,"score_spread":0.3686819932437714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243295","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.988549,0.00004191941,0.003468323,0.006436018,0.0007045145,0.00011317664,0.000578739,0.0000070925053,0.000101212296],"genre_scores_gemma":[0.99823827,0.000046136793,0.0005370083,0.00086282747,0.00006841995,0.0000044069284,0.00020559932,0.0000019103713,0.00003539743],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981582,0.00017937842,0.00034294382,0.00020117656,0.0009476505,0.00017060616],"domain_scores_gemma":[0.99901557,0.00021083553,0.00023121576,0.00016704669,0.00016589476,0.00020942382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062644635,0.00003906065,0.00011346435,0.00051374803,0.0009431401,0.00014277929,0.0011613263,0.000015078059,0.00013027215],"category_scores_gemma":[0.00155793,0.0000384929,0.000030774132,0.00069764914,0.00014961272,0.0012286273,0.00018901107,0.000087988265,1.4040668e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002472838,0.00003337087,0.95854104,0.0000027828332,0.000016476937,0.0000014180494,0.002009144,0.0059618396,0.000004075219,0.031055545,0.000041758994,0.0023078069],"study_design_scores_gemma":[0.00024755226,0.000020260943,0.9412581,0.0000030451258,0.000025062533,0.000003282456,0.0046815206,0.0330408,4.304995e-7,0.0032966903,0.017361177,0.000062105144],"about_ca_topic_score_codex":0.047116116,"about_ca_topic_score_gemma":0.12478543,"teacher_disagreement_score":0.077669315,"about_ca_system_score_codex":0.0004604164,"about_ca_system_score_gemma":0.00066527404,"threshold_uncertainty_score":0.95922923},"labels":[],"label_agreement":null},{"id":"W4294243308","doi":"10.23889/ijpds.v7i3.1828","title":"Changes in healthcare costs and survival in the era of immunotherapy and targeted systemic therapy for melanoma.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; Canadian Agency for Drugs and Technologies in Health; Sunnybrook Hospital; Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto","funders":"","keywords":"Medicine; Propensity score matching; Health care; Cohort; Sentinel lymph node; Retrospective cohort study; Proportional hazards model; Cancer; Internal medicine; Breast cancer","score_opus":0.04733663140156876,"score_gpt":0.36067336662846505,"score_spread":0.3133367352268963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9871533,0.00072671386,0.00039836505,0.010044165,0.00079373363,0.00070454244,0.00016731453,0.0000038159396,0.000008049036],"genre_scores_gemma":[0.9982914,0.00063338445,0.00033379367,0.00051321846,0.00006234205,0.00003978587,0.00010351824,0.000004312915,0.000018264065],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990635,0.000052639167,0.00022327904,0.0001569175,0.00040947853,0.00009417146],"domain_scores_gemma":[0.9995012,0.000092740294,0.000142071,0.00012943326,0.0001099477,0.000024587795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017060961,0.000048563095,0.000101470745,0.00024682668,0.00015220481,0.000049019814,0.00032077174,0.000011155502,0.000009167431],"category_scores_gemma":[0.000095305615,0.00003662304,0.000013206663,0.00017482748,0.00003941271,0.00015876457,0.00007704388,0.00011514999,3.6875306e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003955274,0.00030354943,0.50031537,0.00008613152,0.00008926313,0.0000407409,0.0026682145,0.00025788933,0.024665885,0.010683907,0.00036582033,0.45656794],"study_design_scores_gemma":[0.007093213,0.0013900691,0.94306463,0.00019040339,0.000011658418,0.0023007619,0.0038389298,0.027031675,0.00022164534,0.001335095,0.013354207,0.00016768563],"about_ca_topic_score_codex":0.0005175279,"about_ca_topic_score_gemma":0.0006239799,"teacher_disagreement_score":0.45640025,"about_ca_system_score_codex":0.00014002605,"about_ca_system_score_gemma":0.000054925462,"threshold_uncertainty_score":0.14934443},"labels":[],"label_agreement":null},{"id":"W4294243311","doi":"10.23889/ijpds.v7i3.1882","title":"Advancing multi-regional research in Canada through collaboration.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"General partnership; Alliance; Data governance; Survey data collection; Data sharing; Incentive; Big data; Data access; Corporate governance; Data collection; Business; Geography; Medicine; Data quality; Marketing; Computer science; Database; Finance; Data mining; Sociology","score_opus":0.18392721363493897,"score_gpt":0.49456610073015894,"score_spread":0.31063888709522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243311","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95757586,0.00083632546,0.007166443,0.02342536,0.008922433,0.0010293555,0.0008935721,0.000017154483,0.00013351432],"genre_scores_gemma":[0.9881705,0.00012585022,0.009889843,0.00074654474,0.00034604117,0.00002342006,0.0006156298,0.000008475128,0.00007366662],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9963227,0.00008842065,0.00037503254,0.0003105403,0.0025804942,0.00032279536],"domain_scores_gemma":[0.9984393,0.00012316306,0.00011873758,0.0003082947,0.0008538277,0.00015669156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003212433,0.00006188843,0.0001235415,0.00040412243,0.00081435405,0.00008222601,0.000809935,0.000013287405,0.0000685251],"category_scores_gemma":[0.0007278923,0.000057783738,0.000035729172,0.0009227642,0.00006323623,0.0010584488,0.00032142052,0.00040683817,0.0000012825453],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.0011707932,0.00041650463,0.83195907,0.00005447583,0.0001377485,0.0004617614,0.001184534,0.055407498,0.0012223001,0.004761406,0.057591844,0.045632076],"study_design_scores_gemma":[0.0031976388,0.00010299681,0.4852819,0.00007630582,0.0000138253345,0.0012003506,0.004475744,0.08347254,0.000052443684,0.00069488847,0.42125288,0.00017846977],"about_ca_topic_score_codex":0.5192959,"about_ca_topic_score_gemma":0.55368924,"teacher_disagreement_score":0.36366102,"about_ca_system_score_codex":0.003893919,"about_ca_system_score_gemma":0.008835288,"threshold_uncertainty_score":0.99992996},"labels":[],"label_agreement":null},{"id":"W4294243313","doi":"10.23889/ijpds.v7i3.1962","title":"A proposed approach for standardized reporting of data linkage processes and results.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Linkage (software); Record linkage; Computer science; Linked data; Population; Data science; Information retrieval; Data mining; Readability; Medicine","score_opus":0.5125041464715098,"score_gpt":0.5428579715218413,"score_spread":0.030353825050331573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243313","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017457291,0.0000911537,0.94452274,0.0033307679,0.0015449487,0.0010229895,0.031589054,0.000022197224,0.00041885002],"genre_scores_gemma":[0.75684744,0.000020618365,0.23590769,0.00017158067,0.00020436897,0.000020607093,0.006416657,0.000008181715,0.00040283182],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99315023,0.000094625866,0.0024492163,0.00082139025,0.0033032815,0.00018124591],"domain_scores_gemma":[0.9918025,0.000739334,0.0043823323,0.0013017317,0.0016887088,0.00008539608],"candidate_categories":["metaresearch","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.05103772,0.00008346187,0.00022229993,0.00045012924,0.0008590074,0.00088404457,0.006725245,0.000014883513,0.000019544264],"category_scores_gemma":[0.07579295,0.000065320004,0.00003310964,0.0007029386,0.00017729268,0.0048324624,0.004130147,0.00011406396,2.5457433e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0059731696,0.0011968088,0.013935383,0.00033439827,0.00034325075,0.000028717894,0.0033320899,0.01270308,0.0028507214,0.054566525,0.1642205,0.74051535],"study_design_scores_gemma":[0.003919468,0.00033116867,0.0058322875,0.00005667195,0.000065213186,0.00022995779,0.005229995,0.43843213,0.0002862372,0.04650584,0.49874792,0.00036310856],"about_ca_topic_score_codex":0.00006844195,"about_ca_topic_score_gemma":0.000027969678,"teacher_disagreement_score":0.74015224,"about_ca_system_score_codex":0.00007204648,"about_ca_system_score_gemma":0.00048888545,"threshold_uncertainty_score":0.9986488},"labels":[],"label_agreement":null},{"id":"W4294243330","doi":"10.23889/ijpds.v7i3.1944","title":"Experiences of Red River Métis Accessing COVID Vaccines: A partnership-based, whole-population linked administrative data study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Medicine; Socioeconomic status; Pandemic; Population; Demography; Environmental health; Confounding; Metis; Cohort; Coronavirus disease 2019 (COVID-19); Disease","score_opus":0.5178526423545106,"score_gpt":0.5892360181518559,"score_spread":0.07138337579734533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243330","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9803366,0.000055109143,0.004127244,0.004116155,0.006441926,0.0017490658,0.0029865175,0.00006378656,0.0001235974],"genre_scores_gemma":[0.9888982,0.0000062592394,0.0039603626,0.00051764527,0.0005494282,0.0001689798,0.00577573,0.000016356158,0.000107046544],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99451214,0.00064867357,0.0015041223,0.00077852147,0.0020651275,0.0004914089],"domain_scores_gemma":[0.99519217,0.0007012892,0.0017636794,0.001144699,0.00094181753,0.00025634305],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0059719286,0.00018505879,0.00030648813,0.00068558723,0.0054517784,0.00016497089,0.004884619,0.00007023751,0.0007432261],"category_scores_gemma":[0.0033010733,0.000181494,0.000055519562,0.0008770659,0.0001894707,0.004202055,0.0022028752,0.00063617807,0.000006298646],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013526533,0.0010173869,0.91495794,0.000101061974,0.00010962578,0.000023020699,0.054986957,0.0069846897,0.00012721939,0.0043006083,0.01222741,0.003811443],"study_design_scores_gemma":[0.004768553,0.0008020947,0.58622926,0.00023608089,0.00011913705,0.00003274585,0.16409191,0.20127057,0.000007631662,0.0034035796,0.03849893,0.000539503],"about_ca_topic_score_codex":0.0013821832,"about_ca_topic_score_gemma":0.0009924666,"teacher_disagreement_score":0.32872868,"about_ca_system_score_codex":0.00059020886,"about_ca_system_score_gemma":0.0016217715,"threshold_uncertainty_score":0.995843},"labels":[],"label_agreement":null},{"id":"W4294243356","doi":"10.23889/ijpds.v7i3.1801","title":"Understanding how cancer survivors’ needs and experiences after treatment impact their health care utilization: a survey-administrative health data linkage study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cancer survivorship and care","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"","keywords":"Medicine; Family medicine; Survivorship curve; Breast cancer; Health care; Population; Psychological intervention; Cancer registry; Cancer; Prostate cancer; Colorectal cancer; Gerontology; Nursing; Environmental health; Internal medicine","score_opus":0.5224033844435775,"score_gpt":0.5193055627098333,"score_spread":0.003097821733744177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243356","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96710205,0.0029748522,0.006208253,0.0065074316,0.0033408403,0.0010284701,0.012797472,0.000025868412,0.000014788947],"genre_scores_gemma":[0.99450016,0.00033232928,0.00011729061,0.00042119116,0.0002793852,0.00008887239,0.004192821,0.000014021652,0.00005393469],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99741,0.00024689155,0.00038842362,0.0005553765,0.0011020221,0.00029730142],"domain_scores_gemma":[0.99828815,0.00011980235,0.00040305665,0.0006000191,0.000307637,0.00028131908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021140454,0.00017623152,0.00027758413,0.00038806332,0.0011222904,0.0004661919,0.0009103438,0.000017921519,0.00012250051],"category_scores_gemma":[0.00013973485,0.00013515909,0.000042946245,0.00063046115,0.00013011809,0.001362693,0.0005707566,0.00016372996,1.3206078e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008443239,0.00027740354,0.86444217,0.000024217838,0.0001694916,0.000016425318,0.11006077,0.000090707654,0.0000038538506,0.00010018012,0.0011210366,0.022849426],"study_design_scores_gemma":[0.0018495925,0.0027396746,0.50503945,0.000089945075,0.000031500524,0.00020577636,0.4753147,0.0073270495,0.0000056170675,0.000041524905,0.0071013896,0.00025375548],"about_ca_topic_score_codex":0.016583027,"about_ca_topic_score_gemma":0.080841295,"teacher_disagreement_score":0.36525393,"about_ca_system_score_codex":0.002600027,"about_ca_system_score_gemma":0.0022121705,"threshold_uncertainty_score":0.9899656},"labels":[],"label_agreement":null},{"id":"W4294243366","doi":"10.23889/ijpds.v7i3.1924","title":"A population data-driven approach to identifying ‘Long COVID’ cases in support of diagnosis and treatment.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Long-Term Effects of COVID-19","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"First Nations Health and Social Secretariat of Manitoba; University of Manitoba","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Medical prescription; Sample (material); Population; Medical record; Medicine; Diagnosis code; Test (biology); Family medicine; Environmental health; Nursing; Pathology; Disease","score_opus":0.1612069204338945,"score_gpt":0.4500260002345856,"score_spread":0.2888190798006911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243366","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9893269,0.000047234793,0.0049754423,0.002454425,0.0007364084,0.00087290397,0.0015415866,0.000016302109,0.000028820199],"genre_scores_gemma":[0.9848064,0.000039203118,0.009903685,0.0005265411,0.00014978957,0.00006413262,0.0044573396,0.000011649414,0.000041211246],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976201,0.00006397876,0.0005087263,0.00051795196,0.0010957781,0.0001934714],"domain_scores_gemma":[0.9983958,0.000343291,0.00031860697,0.00057250325,0.00016296549,0.00020685252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015185721,0.00011327683,0.00022221134,0.0008563897,0.00030798154,0.0001646834,0.0011765631,0.000021523045,0.0000537578],"category_scores_gemma":[0.0025518313,0.00010526246,0.00003535257,0.00043823093,0.000065085645,0.002110857,0.0009949881,0.000113828886,9.737006e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026222732,0.00028057882,0.98237395,0.000036380432,0.000041065116,0.000084785606,0.00027361428,0.0052442322,0.00023746655,0.00048837974,0.00096217904,0.009715122],"study_design_scores_gemma":[0.0019743838,0.00043254383,0.9355243,0.000068689274,0.000078916964,0.0011256532,0.000147193,0.05655189,0.000042586867,0.00024617327,0.0036562618,0.0001514464],"about_ca_topic_score_codex":0.0024697047,"about_ca_topic_score_gemma":0.00046691,"teacher_disagreement_score":0.051307656,"about_ca_system_score_codex":0.00070025655,"about_ca_system_score_gemma":0.00027970807,"threshold_uncertainty_score":0.42924786},"labels":[],"label_agreement":null},{"id":"W4294243382","doi":"10.23889/ijpds.v7i3.1796","title":"Potentially inappropriate prescribing in long-term care residents and its association with probable delirium.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Intensive Care Unit Cognitive Disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa; Bruyère; Ottawa Hospital","funders":"","keywords":"Beers Criteria; Medicine; Polypharmacy; Delirium; Dementia; Odds ratio; Confidence interval; Population; Medical prescription; Logistic regression; Deprescribing; Emergency medicine; Psychiatry; Intensive care medicine; Environmental health; Internal medicine; Disease","score_opus":0.034126815762536775,"score_gpt":0.33935044547322135,"score_spread":0.30522362971068456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243382","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938119,0.00016255178,0.0017214654,0.0024985352,0.0008802273,0.0006008469,0.00018714515,0.000013198971,0.00012412436],"genre_scores_gemma":[0.9964112,0.000030441748,0.000920453,0.0013542038,0.00009232949,0.000021117039,0.0009648197,0.000011918428,0.0001934855],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978421,0.00004617291,0.00028390123,0.0003312618,0.0012824278,0.00021414443],"domain_scores_gemma":[0.9915536,0.000040509643,0.00028404512,0.00013983487,0.00790825,0.00007373452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008998288,0.00008850979,0.00011494475,0.00048029947,0.0003905792,0.00018996082,0.0005023205,0.000024157138,0.000031031806],"category_scores_gemma":[0.004054297,0.00008252923,0.000022830884,0.00030326392,0.00003471185,0.0013332992,0.00038836617,0.0002688904,0.0000011319402],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006715206,0.00006620491,0.98928165,0.00003124241,0.00005964182,0.00008685612,0.00052078976,0.0008199129,0.0026888237,0.00028858616,0.00048690606,0.004997871],"study_design_scores_gemma":[0.0024375725,0.00024281106,0.98964643,0.00022176174,0.0000517415,0.00039972743,0.0017334766,0.004399694,0.0003563109,0.00014487609,0.00022424443,0.00014136927],"about_ca_topic_score_codex":0.00012259658,"about_ca_topic_score_gemma":0.00024795288,"teacher_disagreement_score":0.0066258223,"about_ca_system_score_codex":0.00086177717,"about_ca_system_score_gemma":0.0003233281,"threshold_uncertainty_score":0.48536652},"labels":[],"label_agreement":null},{"id":"W4294243386","doi":"10.23889/ijpds.v7i3.1839","title":"An investigation of kindergarten educator reported barriers and concerns and school neighbourhood composition in Ontario, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University","funders":"","keywords":"Neighbourhood (mathematics); Poisson regression; Psychology; Coronavirus disease 2019 (COVID-19); Census; Socioeconomic status; Medical education; Medicine; Environmental health; Population","score_opus":0.0909843201231829,"score_gpt":0.4308891701008607,"score_spread":0.3399048499776778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243386","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964603,0.000029066548,0.00013625533,0.0011513626,0.0017503679,0.00017491057,0.00024763297,0.0000037027667,0.00004641001],"genre_scores_gemma":[0.9984091,0.0000031988748,0.00031920956,0.0006355807,0.00007422028,0.000010920568,0.00049540173,0.000004185394,0.000048167774],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986856,0.000062707186,0.00036777847,0.00027109229,0.0004841903,0.00012865222],"domain_scores_gemma":[0.99910337,0.00004838759,0.00031350143,0.00018012001,0.000116604904,0.00023802381],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093815447,0.00005772771,0.000083909996,0.0002288043,0.0003139394,0.000061349514,0.00040199384,0.00001564338,0.00052389107],"category_scores_gemma":[0.000086761036,0.00006243137,0.0000075760477,0.00014255366,0.000084139254,0.0008084611,0.00012150503,0.00016956875,1.2375804e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010069806,0.000023718289,0.9941882,0.0000029929179,0.000010654964,0.000007208443,0.00084222684,0.000119868746,0.0008999254,0.0018749968,0.00073050027,0.001199014],"study_design_scores_gemma":[0.00064397726,0.000092375376,0.992885,0.000013653588,0.0000071629674,0.00016281195,0.0015442553,0.00253725,0.000027853961,0.00086803513,0.0011515057,0.00006613442],"about_ca_topic_score_codex":0.87921953,"about_ca_topic_score_gemma":0.8403116,"teacher_disagreement_score":0.038907938,"about_ca_system_score_codex":0.0012197479,"about_ca_system_score_gemma":0.0036682594,"threshold_uncertainty_score":0.6507335},"labels":[],"label_agreement":null},{"id":"W4294243394","doi":"10.23889/ijpds.v7i3.1957","title":"Is PAX-Good Behaviour Game (PAX) Associated with Better Mental Health and Educational Outcomes for First Nations Children?","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Community Health and Development","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Red River College; Cree Board of Health and Social Services of James Bay; University of Manitoba; First Nations Health and Social Secretariat of Manitoba; Manitoba Health","funders":"","keywords":"Prosocial behavior; Mental health; Propensity score matching; Population; Indigenous; Cluster randomised controlled trial; Medicine; Cohort; Psychology; Demography; Psychiatry; Environmental health; Intervention (counseling); Sociology","score_opus":0.11953139378137158,"score_gpt":0.49599639743307017,"score_spread":0.3764650036516986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7682498,0.00010038294,0.0018884738,0.21371202,0.0037939153,0.0023563816,0.009768294,0.00003830139,0.00009244093],"genre_scores_gemma":[0.9701075,0.000054646363,0.0062664608,0.012688455,0.00023681395,0.0003248245,0.00953579,0.000019949499,0.00076554285],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99729824,0.00013527417,0.00068429817,0.00034568153,0.0011096754,0.00042684353],"domain_scores_gemma":[0.99728864,0.0008233697,0.00070356054,0.00029245278,0.00059264124,0.00029931034],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0024029098,0.00013142495,0.00017593632,0.00050484383,0.008317748,0.00011286229,0.0011165502,0.00003291353,0.00031577435],"category_scores_gemma":[0.0011868532,0.00011714868,0.0000388779,0.00033560654,0.00008054481,0.00095989654,0.0006324436,0.0004371916,0.000003364303],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006484243,0.00017012775,0.9727148,0.000011824734,0.00004564808,1.5276726e-7,0.0021643057,0.000025646315,8.8412776e-7,0.003721661,0.019916542,0.0011635665],"study_design_scores_gemma":[0.0018668215,0.00015211588,0.9681157,0.00009787357,0.000010920309,0.000032162672,0.0009891873,0.0017742683,3.3328527e-7,0.0017246383,0.025088934,0.00014707205],"about_ca_topic_score_codex":0.0005774145,"about_ca_topic_score_gemma":0.0028614907,"teacher_disagreement_score":0.20185773,"about_ca_system_score_codex":0.0011716697,"about_ca_system_score_gemma":0.0023279474,"threshold_uncertainty_score":0.99297327},"labels":[],"label_agreement":null},{"id":"W4294243407","doi":"10.23889/ijpds.v7i3.1850","title":"Impact of the Choosing Wisely Canada recommendations on potentially inappropriate antibiotic prescribing in emergency medicine across Alberta, Canada: An interrupted time-series analysis.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare cost, quality, practices","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Emergency department; Bronchitis; Emergency medicine; Bronchiolitis; Pharmacy; Interrupted Time Series Analysis; Otitis; Antibiotics; Autoregressive integrated moving average; Pediatrics; Asthma; Interrupted time series; Medical emergency; Family medicine; Internal medicine; Psychological intervention; Surgery","score_opus":0.4215947841011263,"score_gpt":0.5600606805081906,"score_spread":0.1384658964070643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243407","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9686901,0.000015560945,0.0004497561,0.022512285,0.0060750046,0.0004780566,0.0016683034,0.0000065348445,0.00010442267],"genre_scores_gemma":[0.9975007,0.000017552658,0.00038949316,0.0005545649,0.00020252581,0.00000952437,0.0009458114,0.0000122182955,0.00036761127],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9950303,0.0010868042,0.0014436835,0.00040862913,0.0015973058,0.00043327085],"domain_scores_gemma":[0.9960327,0.0004436775,0.0017071448,0.0006236583,0.0010153552,0.00017742792],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0057258313,0.00013925051,0.00026591017,0.00036510453,0.0021870823,0.000038914735,0.0023573746,0.00003281712,0.0008022317],"category_scores_gemma":[0.0059120534,0.00010567253,0.000060056842,0.0014409734,0.000092413255,0.0018730416,0.0007536221,0.0007342115,5.8034556e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027544258,0.000111932604,0.9698459,0.00002030518,0.00021635814,0.0000036433908,0.0021209456,0.01550106,0.0004413784,0.00047019907,0.006045207,0.0049476447],"study_design_scores_gemma":[0.00041286956,0.00010476098,0.9735065,0.000118056174,0.000049436632,0.000009741719,0.0021808401,0.019465746,0.000006254993,0.00017788242,0.003846789,0.00012112676],"about_ca_topic_score_codex":0.99470145,"about_ca_topic_score_gemma":0.99808335,"teacher_disagreement_score":0.028810622,"about_ca_system_score_codex":0.0035058218,"about_ca_system_score_gemma":0.007147972,"threshold_uncertainty_score":0.99911195},"labels":[],"label_agreement":null},{"id":"W4294243450","doi":"10.23889/ijpds.v7i3.1925","title":"Developing non-response weights to account for attrition-related bias in a longitudinal pregnancy cohort.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Innovates; Children's Hospital Foundation; Alberta Children's Hospital Foundation; University of Pittsburgh","keywords":"Statistics; Lasso (programming language); Logistic regression; Receiver operating characteristic; Confidence interval; Cohort; Medicine; Attrition; Calibration; Cohort study; Mathematics; Demography; Computer science","score_opus":0.13032686310966007,"score_gpt":0.3997673923791502,"score_spread":0.26944052926949014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243450","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95133674,0.000017003875,0.041861586,0.003692818,0.0013525358,0.0012207549,0.00045235184,0.000014960872,0.000051225725],"genre_scores_gemma":[0.98097837,0.000016497239,0.017648699,0.00056732463,0.00006861883,0.00023390818,0.00029740992,0.00001685877,0.00017230479],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966172,0.000114634684,0.0006393601,0.00078700023,0.0014041411,0.0004376551],"domain_scores_gemma":[0.99870574,0.0003612052,0.00032762517,0.00035433826,0.00008052628,0.0001705875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005214486,0.00014364252,0.00014565696,0.00046443634,0.0010571703,0.00020094684,0.0018478545,0.00003025117,0.0004807127],"category_scores_gemma":[0.0015645787,0.00015074619,0.00004860156,0.0007104446,0.00011158716,0.0021882697,0.0011030838,0.00023316065,0.000042196407],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054683106,0.00018064275,0.9452803,0.000007483386,0.000026972864,0.000035288922,0.00062033767,0.026005581,0.003099585,0.0010212311,0.00071802427,0.022457704],"study_design_scores_gemma":[0.0008999766,0.00009998316,0.9486281,0.0001060777,0.000008392708,0.000103146944,0.00012154508,0.03737143,0.00014937908,0.002529,0.009757835,0.00022509453],"about_ca_topic_score_codex":0.0005306492,"about_ca_topic_score_gemma":0.0002950281,"teacher_disagreement_score":0.029641615,"about_ca_system_score_codex":0.0025965215,"about_ca_system_score_gemma":0.00020313906,"threshold_uncertainty_score":0.81310064},"labels":[],"label_agreement":null},{"id":"W4294243457","doi":"10.23889/ijpds.v7i3.1853","title":"Combining immigration records with a postpartum population-based survey to assess prevalence of perinatal psychosocial and behavioral risk factors among immigrant subgroups.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Medicine; Odds ratio; Psychosocial; Immigration; Population; Demography; Public health; Socioeconomic status; Environmental health; Psychiatry; Geography; Nursing","score_opus":0.08398543692482469,"score_gpt":0.41339021409924587,"score_spread":0.3294047771744212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243457","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9864448,0.000021946427,0.006180039,0.00016994882,0.0024632637,0.0005037843,0.0041893385,0.000020249076,0.000006643744],"genre_scores_gemma":[0.9961765,0.000007317174,0.0014264378,0.000053318337,0.00009340096,0.000051868057,0.0021244886,0.000017551256,0.000049126822],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99698615,0.00029017703,0.00067152566,0.0005568377,0.0011931808,0.0003021252],"domain_scores_gemma":[0.9977369,0.00025423925,0.00081777835,0.00036897958,0.0006099674,0.00021217385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027118353,0.00016467173,0.0001951958,0.0005318755,0.0010248361,0.00019270781,0.0010538035,0.000042857777,0.00019654557],"category_scores_gemma":[0.0003204142,0.00015427684,0.000045852517,0.00054321875,0.00011183635,0.0012411828,0.00014412777,0.0002858032,8.792236e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063231227,0.00014950785,0.9947561,0.000011164046,0.000019798945,0.0000021162107,0.0019027061,0.00069919,0.000022479551,0.00036781913,0.00011892016,0.0013179118],"study_design_scores_gemma":[0.00082637573,0.000596942,0.9912314,0.00003122408,0.00002896612,0.000032884862,0.000932433,0.0059857615,0.000013813308,0.00008366687,0.00006430469,0.0001722589],"about_ca_topic_score_codex":0.040011894,"about_ca_topic_score_gemma":0.013918893,"teacher_disagreement_score":0.026093002,"about_ca_system_score_codex":0.00020954812,"about_ca_system_score_gemma":0.00020888283,"threshold_uncertainty_score":0.9663808},"labels":[],"label_agreement":null},{"id":"W4294243459","doi":"10.23889/ijpds.v7i3.1873","title":"The Intergenerational Transfer of Mental Disorders: A Population-based Multigenerational Linkage Study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Linkage (software); Psychology; Population; Transfer (computing); Developmental psychology; Genetics; Medicine; Computer science; Biology; Environmental health; Gene","score_opus":0.06732800882462228,"score_gpt":0.4293835140450939,"score_spread":0.3620555052204716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9468608,0.00011882886,0.011097814,0.02579084,0.0129860295,0.0012635881,0.0016325731,0.00003129585,0.0002182545],"genre_scores_gemma":[0.99691594,0.000035453755,0.0009643818,0.000501342,0.0005452312,0.000059198384,0.0007148978,0.000007909451,0.00025564557],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9963303,0.00023935016,0.0006256924,0.00027519965,0.0022504148,0.00027903783],"domain_scores_gemma":[0.9985903,0.00041567776,0.00021183708,0.00024047426,0.00042257353,0.00011914423],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00435909,0.000089904104,0.00010719807,0.00021576039,0.0061023044,0.00039720823,0.0020419736,0.000020615274,0.00032417013],"category_scores_gemma":[0.00090781774,0.00007569188,0.000079536585,0.000331985,0.00018124621,0.0011806225,0.00020013095,0.0001693278,9.4227494e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023901588,0.0005276397,0.8114655,0.0000066410375,0.00007246081,0.0000013746169,0.0045427196,0.022793341,0.00007761126,0.13890968,0.0031391657,0.018224861],"study_design_scores_gemma":[0.0017787601,0.00017074507,0.74138474,0.000020886597,0.000022328177,0.000005667875,0.007920493,0.0993994,0.000018140749,0.0035320783,0.1454763,0.00027042732],"about_ca_topic_score_codex":0.005655666,"about_ca_topic_score_gemma":0.01609707,"teacher_disagreement_score":0.14233713,"about_ca_system_score_codex":0.0004570188,"about_ca_system_score_gemma":0.00089762954,"threshold_uncertainty_score":0.99519163},"labels":[],"label_agreement":null},{"id":"W4294243523","doi":"10.23889/ijpds.v7i3.1851","title":"Developing Machine Learning Algorithms on Routinely Collected Administrative Health Data - Lessons from Ontario, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Machine learning; Health care; Artificial intelligence; Computer science; Timeline; Population health; Decision tree; Feature (linguistics); Multidisciplinary approach; Medicine; Population; Data science; Data mining; Statistics; Mathematics; Environmental health; Political science","score_opus":0.22516180118092236,"score_gpt":0.44736434881856224,"score_spread":0.22220254763763989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243523","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.039850153,0.00017699547,0.7943265,0.14054802,0.014552435,0.00084118673,0.009288547,0.0001923479,0.00022382988],"genre_scores_gemma":[0.8373965,0.000014005336,0.1496682,0.0028318919,0.00031951035,0.000016923319,0.009208998,0.000017614439,0.00052635756],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9951631,0.00030073425,0.00070504873,0.0010036107,0.0023525618,0.00047494017],"domain_scores_gemma":[0.9969214,0.00041988108,0.00087902346,0.0010833988,0.00045361396,0.00024267093],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.00313995,0.00017513533,0.00021209376,0.00032387936,0.0032858758,0.0007283075,0.010326379,0.000021582817,0.00012991547],"category_scores_gemma":[0.0015972262,0.00017850382,0.000024849995,0.0007491795,0.00004613478,0.002014668,0.0041039637,0.0009630433,0.0000017024797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.0004864358,0.00040430232,0.27976924,0.000029602967,0.00035292667,0.00034294036,0.006705334,0.12983915,0.00007545582,0.1843201,0.05303453,0.34464],"study_design_scores_gemma":[0.0004401624,0.0001532047,0.1263448,0.000040855026,0.0000031992067,0.00014429832,0.0001335472,0.7610809,0.000006326281,0.0010301168,0.110408,0.00021454047],"about_ca_topic_score_codex":0.88761985,"about_ca_topic_score_gemma":0.89495003,"teacher_disagreement_score":0.7975463,"about_ca_system_score_codex":0.0038466256,"about_ca_system_score_gemma":0.014095416,"threshold_uncertainty_score":0.9999774},"labels":[],"label_agreement":null},{"id":"W4294243548","doi":"10.23889/ijpds.v7i3.1934","title":"Inclusion, Diversity, Equity, and Accessibility (IDEA) in multi-regional data research: An approach to facilitating change in a distributed research environment.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Manitoba Health","funders":"","keywords":"Inclusion (mineral); Equity (law); Diversity (politics); Data science; Computer science; Political science; Sociology; Social science","score_opus":0.7307779971902879,"score_gpt":0.5776754475089709,"score_spread":0.15310254968131698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9761731,0.00009111115,0.0051729763,0.013495376,0.0003904093,0.0012141204,0.0033646459,0.000030143981,0.0000681317],"genre_scores_gemma":[0.98972684,0.000046232104,0.0086383475,0.00012544503,0.00008371152,0.000054710265,0.0013041075,0.0000054444777,0.000015176498],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9923392,0.0009335199,0.00040660775,0.0009786435,0.00473341,0.0006086394],"domain_scores_gemma":[0.9980122,0.00046187657,0.00012910302,0.000764711,0.00040182477,0.00023030165],"candidate_categories":["metaresearch","sts","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.04480319,0.00008617518,0.00012184086,0.0014417764,0.0060143596,0.0004528457,0.011483754,0.000057626614,0.000032298274],"category_scores_gemma":[0.0060672946,0.00009386249,0.000012659656,0.0016642426,0.0009365338,0.0052073593,0.1251767,0.0007912652,0.0000016949955],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019389957,0.0009624078,0.8772537,0.000009806713,0.0000090755275,0.000021708662,0.043234523,0.00059887295,0.00024894738,0.008793128,0.0006409819,0.06803296],"study_design_scores_gemma":[0.0009827042,0.00007923706,0.8453445,0.00003477102,0.000002086465,0.000015160009,0.018410256,0.1045185,0.0000024878543,0.024388554,0.00604203,0.00017971004],"about_ca_topic_score_codex":0.028469888,"about_ca_topic_score_gemma":0.024687268,"teacher_disagreement_score":0.11369295,"about_ca_system_score_codex":0.0016232915,"about_ca_system_score_gemma":0.0003465425,"threshold_uncertainty_score":0.99527967},"labels":[],"label_agreement":null},{"id":"W4294243563","doi":"10.23889/ijpds.v7i3.1807","title":"COVID-19 vaccine coverage and factors associated with vaccine uptake among individuals with a recent experience of homelessness: a population-based analysis from Ontario, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Western University","funders":"","keywords":"Medicine; Receipt; Poisson regression; Population; Influenza vaccine; Demography; Cohort; Relative risk; Coronavirus disease 2019 (COVID-19); Retrospective cohort study; Cohort study; Vaccination; Environmental health; Confidence interval; Immunology; Internal medicine; Disease","score_opus":0.07180540372458093,"score_gpt":0.397961751930945,"score_spread":0.3261563482063641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243563","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912682,0.000029852146,0.0035056293,0.00038621656,0.0005109387,0.00041926364,0.0038553167,0.000017126667,0.0000074315853],"genre_scores_gemma":[0.99295604,0.000010807412,0.00026480271,0.00021485562,0.00005347612,0.000054098975,0.006394343,0.000013755331,0.00003780879],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9963939,0.00021191436,0.00076879014,0.00047381924,0.0018336994,0.00031788327],"domain_scores_gemma":[0.99661255,0.0006259304,0.001335086,0.000340541,0.0007475181,0.00033837158],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00128952,0.00017324832,0.00049974356,0.0004850837,0.002010176,0.00010337779,0.0010903733,0.000048160677,0.0012712185],"category_scores_gemma":[0.001255229,0.00013534422,0.000035280824,0.0012770669,0.00005872515,0.00097509735,0.0002975034,0.00035563967,6.527149e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015655487,0.000059538997,0.9802091,0.0000056928857,0.00024134004,0.000005771799,0.0073244427,0.0115901055,0.0000064129613,0.00012984283,0.00003717365,0.00023401863],"study_design_scores_gemma":[0.0016015607,0.00006311123,0.9782025,0.000047573874,0.00014809397,3.1851044e-7,0.013669352,0.0048939623,0.000003956514,0.00014180408,0.0010582888,0.00016945509],"about_ca_topic_score_codex":0.9057256,"about_ca_topic_score_gemma":0.991574,"teacher_disagreement_score":0.08584835,"about_ca_system_score_codex":0.0023645528,"about_ca_system_score_gemma":0.0038899386,"threshold_uncertainty_score":0.9996418},"labels":[],"label_agreement":null},{"id":"W4294243567","doi":"10.23889/ijpds.v7i3.1782","title":"Data on Patient Record Trajectory for Linkage (DataPRinT Linkage).","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Linkage (software); Computer science; Data mining; Table (database); Key (lock); Medical diagnosis; Process (computing); Medical record; Health care; Record linkage; Information retrieval; Data science; Computer security; Medicine; Political science","score_opus":0.4308056502261164,"score_gpt":0.5122798057911399,"score_spread":0.08147415556502347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243567","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14074223,0.000114072056,0.64453757,0.024659086,0.05348919,0.0028910395,0.1319569,0.00013956179,0.0014703225],"genre_scores_gemma":[0.9164508,0.000060573533,0.054106664,0.0052750194,0.0015409528,0.00012155135,0.020599853,0.000035660785,0.0018089075],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99244416,0.00019835998,0.0012127474,0.00125414,0.0045370962,0.00035349317],"domain_scores_gemma":[0.99414223,0.0011649794,0.0009479825,0.002841748,0.0007167674,0.00018626527],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.01718742,0.00015610264,0.00020337425,0.0008331821,0.0015513302,0.0015848781,0.016583357,0.00002756258,0.00052877615],"category_scores_gemma":[0.009897495,0.00013329,0.00008936032,0.0006209705,0.00013244599,0.00484185,0.006654784,0.00030876286,0.000045144152],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004378703,0.00040958938,0.0011790607,0.000006345108,0.000059820784,0.000015183608,0.0002367361,0.0074491906,0.00019036677,0.028849114,0.2833042,0.6778625],"study_design_scores_gemma":[0.000586903,0.00024760322,0.0045678373,0.000015044808,0.000013533917,0.000026841086,0.00062490604,0.09449528,0.000025947027,0.016399182,0.8828146,0.00018235562],"about_ca_topic_score_codex":0.00010311247,"about_ca_topic_score_gemma":0.0001383535,"teacher_disagreement_score":0.77570856,"about_ca_system_score_codex":0.00031918104,"about_ca_system_score_gemma":0.00027374583,"threshold_uncertainty_score":0.9997485},"labels":[],"label_agreement":null},{"id":"W4294243576","doi":"10.23889/ijpds.v7i3.1947","title":"Documenting First Nations Access to COVID Vaccines: A whole-population linked administrative data study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; First Nations Health and Social Secretariat of Manitoba; Manitoba Health","funders":"","keywords":"Confounding; Vaccination; Medicine; Public health; Demography; Population; Coronavirus disease 2019 (COVID-19); Cohort study; Cohort; Environmental health; Virology; Internal medicine; Disease","score_opus":0.21063330106968603,"score_gpt":0.5016303648226748,"score_spread":0.2909970637529887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243576","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89457774,0.000079392295,0.022685885,0.05966398,0.012501101,0.0039688107,0.0045696213,0.00018739748,0.0017660424],"genre_scores_gemma":[0.9939282,0.000019934127,0.0016490929,0.0005461553,0.00107004,0.00007256345,0.0021569133,0.000013028936,0.00054408296],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9958222,0.00017914522,0.000675554,0.0007443949,0.0022154974,0.00036319045],"domain_scores_gemma":[0.99719036,0.00043930826,0.00055030896,0.0007996628,0.0007532313,0.00026711833],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0047440343,0.00013870775,0.00016077035,0.00080915296,0.0077039767,0.0023498063,0.008163954,0.000026909793,0.0005106741],"category_scores_gemma":[0.0068616453,0.00014721633,0.000043265212,0.0014813044,0.00002550373,0.009842798,0.002926363,0.00023365735,0.000011280594],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022623813,0.0006474072,0.93349826,0.000009679174,0.00011435413,0.00003486445,0.010129523,0.008317579,0.000053964242,0.012602497,0.024958257,0.009407369],"study_design_scores_gemma":[0.0013383566,0.00021671115,0.6153436,0.00004702007,0.000062672036,0.000037456222,0.009612614,0.010518958,0.0000022945098,0.0029578807,0.35944957,0.00041292302],"about_ca_topic_score_codex":0.0035638597,"about_ca_topic_score_gemma":0.039689932,"teacher_disagreement_score":0.3344913,"about_ca_system_score_codex":0.0007915719,"about_ca_system_score_gemma":0.00080155366,"threshold_uncertainty_score":0.99868584},"labels":[],"label_agreement":null},{"id":"W4294243578","doi":"10.23889/ijpds.v7i3.1938","title":"Disparities in adherence to diabetes screening guidelines among males and females in a universal care setting: A population-based study of 1,389,697 adults.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Diabetes Management and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; University of Calgary; University of Alberta","funders":"","keywords":"Medicine; Odds ratio; Diabetes mellitus; Prediabetes; Population; Demography; Logistic regression; Confidence interval; Type 2 diabetes; Internal medicine; Environmental health; Endocrinology","score_opus":0.0906646926463351,"score_gpt":0.3974549507913266,"score_spread":0.3067902581449915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243578","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978662,0.000059424,0.00014004824,0.0008876181,0.000414448,0.00052221376,0.00009143882,0.000008619424,0.00000997654],"genre_scores_gemma":[0.99526507,0.0000024535293,0.004001737,0.00011265479,0.00007061179,0.00003249604,0.00047497705,0.000007136623,0.000032894917],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982629,0.0000423203,0.0004931993,0.00030237113,0.00072775234,0.00017145884],"domain_scores_gemma":[0.99903256,0.0000866632,0.00024607265,0.00018760208,0.00037763637,0.000069469854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009854718,0.00008726108,0.0001476279,0.0009558248,0.00018680845,0.00010335057,0.0005441303,0.000013311833,0.000019308576],"category_scores_gemma":[0.00086779404,0.00008907359,0.000020594329,0.0004894019,0.00003708424,0.00091544754,0.00032469485,0.00011272698,1.4701806e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011790609,0.00012316504,0.98044676,0.000027612456,0.000009225847,0.0000029681078,0.00073273736,0.010450341,0.0000324573,0.00009214589,0.000047228074,0.007917479],"study_design_scores_gemma":[0.0011503885,0.00028036087,0.9303616,0.00026074392,0.000014982336,0.0000011325887,0.008819795,0.05891768,0.000007179127,0.000052829975,0.000052171476,0.00008108674],"about_ca_topic_score_codex":0.0030589793,"about_ca_topic_score_gemma":0.0032142494,"teacher_disagreement_score":0.050085083,"about_ca_system_score_codex":0.00017083416,"about_ca_system_score_gemma":0.00009665754,"threshold_uncertainty_score":0.4624282},"labels":[],"label_agreement":null},{"id":"W4294243587","doi":"10.23889/ijpds.v7i3.1898","title":"Socioeconomic gradient in mortality of working age and older adults with multiple long-term conditions in England and Ontario, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Health Care Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Lakehead University; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Socioeconomic status; Term (time); Demography; Gerontology; Geography; Medicine; Population; Sociology","score_opus":0.08231033926973942,"score_gpt":0.42627810196512195,"score_spread":0.34396776269538254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243587","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99768454,0.000052882915,0.00002464433,0.00037920932,0.0009020045,0.00042041644,0.0005135398,0.0000028599113,0.000019888714],"genre_scores_gemma":[0.9991101,0.00001442317,0.00022230427,0.00015558435,0.000043719258,0.000028462777,0.00039568308,0.000004103077,0.000025608982],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99859625,0.000081296326,0.00047102832,0.00024388058,0.00039577793,0.00021174704],"domain_scores_gemma":[0.9991277,0.00021124317,0.00031584696,0.00013670968,0.000118541124,0.000089993635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011487672,0.00006380827,0.00012690318,0.00020499647,0.00048402953,0.000022554226,0.00038762906,0.000019174948,0.000093275165],"category_scores_gemma":[0.00013523246,0.000061009323,0.000006751199,0.00010304058,0.00007934195,0.00046201283,0.0002897812,0.00030081518,1.9569549e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008423518,0.00002331109,0.9963608,0.000017668768,0.0000051541374,0.00002422348,0.0026593201,0.00023746863,0.0000044532494,0.00018113978,0.000096118994,0.00030615696],"study_design_scores_gemma":[0.0015991952,0.000026249914,0.9946083,0.00021123134,0.0000034334748,0.000024443092,0.0008712768,0.0017995994,5.7183195e-7,0.0001603939,0.000635464,0.000059868864],"about_ca_topic_score_codex":0.73871183,"about_ca_topic_score_gemma":0.99523985,"teacher_disagreement_score":0.256528,"about_ca_system_score_codex":0.0013855232,"about_ca_system_score_gemma":0.00096490915,"threshold_uncertainty_score":0.37228128},"labels":[],"label_agreement":null},{"id":"W4294243592","doi":"10.23889/ijpds.v7i3.1823","title":"What do women living with HIV think about research on children born HIV-free in the UK?","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"HIV/AIDS Research and Interventions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Global Health Research","funders":"","keywords":"Medicine; General partnership; Human immunodeficiency virus (HIV); Family medicine; Ethnic group; Teen pregnancy; Pregnancy; Public health; Gerontology; Psychology; Population; Nursing; Environmental health","score_opus":0.09024773518414146,"score_gpt":0.4495671486457284,"score_spread":0.3593194134615869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243592","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97589123,0.0002706238,0.0011515829,0.019240644,0.0005947602,0.00079254893,0.0008272818,0.000017377517,0.0012139528],"genre_scores_gemma":[0.99531525,0.000121328114,0.00057180616,0.00039623518,0.00038275323,0.00006940064,0.00049820007,0.0000113978085,0.002633639],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99500024,0.00023298986,0.00034886657,0.0003794771,0.0035535768,0.000484869],"domain_scores_gemma":[0.9980293,0.00035603883,0.00013031073,0.0007676032,0.00054396526,0.00017278106],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.008657955,0.000088930006,0.00011163128,0.0010087452,0.001101852,0.00108223,0.0035936413,0.000018599632,0.00082149054],"category_scores_gemma":[0.0026000084,0.00005898992,0.00004937718,0.0008854642,0.00021262074,0.0020820326,0.000943385,0.0008676856,0.000017313618],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013754664,0.0016421429,0.49740633,0.000022008264,0.00022114992,0.00016547671,0.011536308,0.002951822,0.00032034182,0.028980821,0.39433295,0.0610452],"study_design_scores_gemma":[0.0026176185,0.0030454483,0.931599,0.001066014,0.000013172259,0.0013804839,0.014924599,0.020818507,0.000021332178,0.004358118,0.019943813,0.00021188258],"about_ca_topic_score_codex":0.0001705441,"about_ca_topic_score_gemma":0.0001038734,"teacher_disagreement_score":0.4341927,"about_ca_system_score_codex":0.0007071306,"about_ca_system_score_gemma":0.00039359994,"threshold_uncertainty_score":0.99995476},"labels":[],"label_agreement":null},{"id":"W4294243601","doi":"10.23889/ijpds.v7i3.1966","title":"POPPY II Cohort Profile– a population-based linked cohort examining the patterns and outcomes of prescription opioid use in NSW, Australia, 2003-2018.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Cohort; Medicine; Codeine; Poppy; Opioid; Medical prescription; Cohort study; Population; Pharmacy; Family medicine; Demography; Psychiatry; Environmental health; Internal medicine; Morphine; Pharmacology; Geography","score_opus":0.088805867333193,"score_gpt":0.37446175727092795,"score_spread":0.28565588993773494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243601","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9951825,0.000025198191,0.0005858331,0.00084167504,0.0012886568,0.0011254085,0.0009303641,0.000014109372,0.0000062299014],"genre_scores_gemma":[0.99401045,0.000018612878,0.0025397022,0.000199357,0.00007215096,0.00010211001,0.0027914252,0.000013504611,0.0002526856],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99729216,0.000071853836,0.0006550586,0.0004112004,0.0013522337,0.00021752034],"domain_scores_gemma":[0.9986108,0.00011176971,0.00035013424,0.00045616287,0.0003827508,0.00008836518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014152227,0.00014312589,0.00022977874,0.00046576906,0.0004683612,0.00014196747,0.0006766644,0.000032778367,0.00010342788],"category_scores_gemma":[0.0008847316,0.00011081068,0.00004046929,0.00040478972,0.00007752963,0.0011271068,0.00035006955,0.00023294186,6.214793e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000106386266,0.00019519887,0.9966604,0.000011453007,0.00006240697,0.0000063424163,0.00018347897,0.0012282154,0.00021995236,0.0002223775,0.00019427271,0.0009094772],"study_design_scores_gemma":[0.0012561586,0.0001745976,0.96913314,0.00006626149,0.00007311071,0.0000449535,0.00015808393,0.02857956,0.000034863224,0.00008459401,0.00029991497,0.00009476818],"about_ca_topic_score_codex":0.0061556906,"about_ca_topic_score_gemma":0.00032746998,"teacher_disagreement_score":0.027527303,"about_ca_system_score_codex":0.00043018095,"about_ca_system_score_gemma":0.00024232594,"threshold_uncertainty_score":0.93056035},"labels":[],"label_agreement":null},{"id":"W4294243604","doi":"10.23889/ijpds.v7i3.1911","title":"A Synthesis of Algorithms for Multi-Jurisdiction Research in Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Algorithm; Computer science; Suite; Mental health; Generalizability theory; Population; Data mining; Machine learning; Medicine; Mathematics; Environmental health; Psychiatry; Statistics; Geography","score_opus":0.6640228554310939,"score_gpt":0.6281443263302975,"score_spread":0.035878529100796364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243604","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.881943,0.00007199206,0.07792991,0.026121518,0.007279332,0.0021304956,0.004451551,0.000014456993,0.000057786547],"genre_scores_gemma":[0.96320903,0.000017609065,0.035814494,0.00018649886,0.0002107417,0.00006902954,0.00045327112,0.000007606535,0.000031691798],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99694103,0.00008712691,0.00083235104,0.0002636418,0.0016866033,0.00018926385],"domain_scores_gemma":[0.9968349,0.0012419557,0.00037525233,0.0002466569,0.0012202965,0.00008095633],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008361373,0.000049240716,0.00012124144,0.00054297334,0.00031570363,0.000040179686,0.0007705355,0.000012219354,0.00006709663],"category_scores_gemma":[0.010082028,0.000049086237,0.000032126318,0.00048640804,0.000056075904,0.0008210089,0.0003065952,0.00023695957,3.4525138e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030901649,0.00089516235,0.38296202,0.000066145374,0.00013196182,0.00003983588,0.00024082378,0.009492293,0.0056888643,0.0022644892,0.01572805,0.5794002],"study_design_scores_gemma":[0.0026684895,0.00021810725,0.22642806,0.0000682896,0.00003579373,0.00020956018,0.0018890115,0.7429625,0.0006287355,0.00082654704,0.023964357,0.00010056464],"about_ca_topic_score_codex":0.33118713,"about_ca_topic_score_gemma":0.21017575,"teacher_disagreement_score":0.7334702,"about_ca_system_score_codex":0.0016446739,"about_ca_system_score_gemma":0.0030317975,"threshold_uncertainty_score":0.99825644},"labels":[],"label_agreement":null},{"id":"W4294243608","doi":"10.23889/ijpds.v7i3.1787","title":"The impact of opioid agonist treatment on fatal and non-fatal drug overdose among people with a history of opioid dependence in NSW, Australia, 2001-2018: findings from the OATS retrospective linkage study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Medicine; Drug overdose; Polysubstance dependence; Opioid overdose; Emergency department; Opioid; Emergency medicine; Cohort; Retrospective cohort study; Anesthesia; Poison control; Substance abuse; Internal medicine; (+)-Naloxone; Psychiatry","score_opus":0.03628656264235535,"score_gpt":0.34930784137275456,"score_spread":0.3130212787303992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243608","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969456,0.0001109443,0.00003239974,0.00018374903,0.000509747,0.00080630276,0.0013811901,0.000004198494,0.000025843507],"genre_scores_gemma":[0.9989353,0.00007486181,0.00017925115,0.00001338823,0.00006280634,0.000041722735,0.000412695,0.000009369638,0.00027061527],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977812,0.000054988515,0.00040801696,0.0003735758,0.0011798824,0.00020233156],"domain_scores_gemma":[0.99870235,0.00021351405,0.00034177888,0.00046515305,0.00019247492,0.00008473157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007772509,0.00015490975,0.00022178302,0.00018731547,0.00034027128,0.00008004414,0.00083139393,0.000017340348,0.00005475547],"category_scores_gemma":[0.00021465008,0.00008838299,0.0000672695,0.00023741918,0.0002418674,0.00059596106,0.00028297436,0.00022168695,6.4710326e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081155455,0.00065263576,0.9911018,0.0000029393966,0.00013660724,0.000022306413,0.0054314686,0.00051673397,0.0004590306,0.000039858012,0.00049394625,0.0003311192],"study_design_scores_gemma":[0.0023386383,0.0015031238,0.9901809,0.000067287474,0.000053162323,0.0000446335,0.0020020767,0.003420417,0.00014047357,0.000106653184,0.00006152504,0.00008108929],"about_ca_topic_score_codex":0.030650195,"about_ca_topic_score_gemma":0.0047916966,"teacher_disagreement_score":0.0258585,"about_ca_system_score_codex":0.0025835927,"about_ca_system_score_gemma":0.0006734126,"threshold_uncertainty_score":0.9758048},"labels":[],"label_agreement":null},{"id":"W4294243609","doi":"10.23889/ijpds.v7i3.1849","title":"The same, only different: Using physician billing data from four provincial payment systems to describe family physician practice patterns in Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; Ontario Shores Centre for Mental Health Sciences; Dalhousie University","funders":"","keywords":"Graduation (instrument); Per capita; Medicine; Medical prescription; Family medicine; Cohort; Payment; Workforce; Emergency department; Population; Service (business); Demography; Medical emergency; Nursing; Business; Finance; Environmental health","score_opus":0.22170700656602071,"score_gpt":0.4641772322513343,"score_spread":0.24247022568531357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243609","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.916627,0.00022167571,0.012188609,0.023282818,0.025375033,0.0019386483,0.020049108,0.000026544483,0.00029056566],"genre_scores_gemma":[0.9667915,0.000051877934,0.0008956298,0.02836793,0.0017702916,0.000053670912,0.0019874717,0.000022199787,0.00005944502],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9955494,0.00043116283,0.00092425634,0.00053878233,0.0019923395,0.0005640662],"domain_scores_gemma":[0.99657065,0.0010781137,0.00083235535,0.0008673176,0.00047219385,0.00017935607],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002699629,0.00014963426,0.00021901232,0.00019858307,0.003598689,0.0002478534,0.004169236,0.000023544266,0.00001376184],"category_scores_gemma":[0.0008433292,0.00011488346,0.000025659536,0.00033781407,0.000027361357,0.0021609822,0.0026172912,0.00065186585,0.0000034576733],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.0016244686,0.0004721997,0.6595698,0.00012215918,0.00033735612,0.00015878837,0.0038671545,0.027271459,0.0019884864,0.0062815775,0.094424315,0.20388226],"study_design_scores_gemma":[0.0012788387,0.000073050454,0.47915196,0.0002502392,0.000063138825,0.000020284751,0.02342982,0.21629345,0.000003644881,0.0005816542,0.27844438,0.00040953318],"about_ca_topic_score_codex":0.803977,"about_ca_topic_score_gemma":0.74863654,"teacher_disagreement_score":0.20347273,"about_ca_system_score_codex":0.0068762936,"about_ca_system_score_gemma":0.009741925,"threshold_uncertainty_score":0.9976985},"labels":[],"label_agreement":null},{"id":"W4294243611","doi":"10.23889/ijpds.v7i3.1942","title":"Building partnerships, capacity, and knowledge through a use of newly linked child development and education datasets in Ontario, Canada.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Infant Development and Preterm Care","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Memorial University of Newfoundland; University of Toronto; McMaster University","funders":"","keywords":"Socioeconomic status; General partnership; Neighbourhood (mathematics); Entropy (arrow of time); Psychology; Demography; Mathematics; Political science; Sociology","score_opus":0.13363826298259948,"score_gpt":0.3637452021054739,"score_spread":0.23010693912287442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243611","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974871,0.000070036614,0.00015439348,0.0006422875,0.00090980437,0.00019315978,0.0004557923,0.0000028366824,0.000084546715],"genre_scores_gemma":[0.9624464,0.0000098204055,0.034481816,0.00025270076,0.000047219142,0.00000866709,0.0027043105,0.000004012426,0.000045062356],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99881625,0.00002171561,0.00032431152,0.00021674507,0.00050213985,0.000118858945],"domain_scores_gemma":[0.9994001,0.000050654144,0.00017030776,0.00013677642,0.00017240313,0.00006975567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058218086,0.00006919148,0.0001023949,0.00021149263,0.00028850092,0.00008470045,0.00031535464,0.000014648535,0.000024306562],"category_scores_gemma":[0.00024238072,0.00006767521,0.000007894192,0.00014545873,0.00004932862,0.0010871986,0.00037347083,0.0001864011,3.2829625e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002323329,0.00007181316,0.9602331,0.000045402478,0.000049278817,0.000012692162,0.0044614356,0.00008669342,0.00034212956,0.006378004,0.00536728,0.022719843],"study_design_scores_gemma":[0.00080254214,0.000031821095,0.61867374,0.00022405051,0.00001568851,0.0005417632,0.000301061,0.0018046435,0.00016245755,0.0004189839,0.37687722,0.00014603774],"about_ca_topic_score_codex":0.22243248,"about_ca_topic_score_gemma":0.66121083,"teacher_disagreement_score":0.43877834,"about_ca_system_score_codex":0.0005909137,"about_ca_system_score_gemma":0.0028370635,"threshold_uncertainty_score":0.7827454},"labels":[],"label_agreement":null},{"id":"W4294243617","doi":"10.23889/ijpds.v7i3.1961","title":"Linking Databases in Collaborative and Culturally Safe Ways to Evaluate the Effectiveness of PAX-Good Behaviour Game (PAX) in First Nations Communities.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Community Health and Development","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Cree Board of Health and Social Services of James Bay; Government of Manitoba; University of Manitoba; First Nations Health and Social Secretariat of Manitoba; Manitoba Health","funders":"","keywords":"Indigenous; Public relations; Promotion (chess); Research ethics; Sociology; Psychology; Political science; Law; Ecology; Politics","score_opus":0.18931567400748023,"score_gpt":0.5037031559729244,"score_spread":0.31438748196544414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98910403,0.00009330016,0.0026198444,0.003482078,0.0013672848,0.001555444,0.0015164721,0.000008144554,0.0002533794],"genre_scores_gemma":[0.99546486,0.000112508176,0.0027542796,0.00043054568,0.000039836297,0.00021920435,0.0009597961,0.0000059827407,0.000012963927],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971985,0.00088066247,0.0006678699,0.00017114897,0.00083424157,0.0002475306],"domain_scores_gemma":[0.9949985,0.0034920794,0.00027617937,0.00035320214,0.00079253915,0.000087466025],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0107550565,0.000088480134,0.000156063,0.0006426006,0.0025783447,0.000054261327,0.0014655782,0.000017303659,0.00006267498],"category_scores_gemma":[0.0023463483,0.0000707398,0.000014406434,0.0009858477,0.00008986399,0.0009218841,0.0017065137,0.00060112035,0.0000014095114],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004654353,0.00014615954,0.94347143,0.000074430674,0.000011525886,0.000002931356,0.014497639,0.007641428,0.00008483743,0.03192457,0.000192022,0.0014875995],"study_design_scores_gemma":[0.0013525482,0.00007003845,0.9679395,0.0006598555,0.000006386734,0.000013792952,0.012780056,0.008020548,0.000008586167,0.0018693482,0.007174231,0.00010511505],"about_ca_topic_score_codex":0.006104532,"about_ca_topic_score_gemma":0.066371575,"teacher_disagreement_score":0.060267042,"about_ca_system_score_codex":0.0007743894,"about_ca_system_score_gemma":0.0010331853,"threshold_uncertainty_score":0.99872017},"labels":[],"label_agreement":null},{"id":"W4294243664","doi":"10.23889/ijpds.v7i3.1813","title":"Creating and Evaluating Two Cumulative Developmental Vulnerability Risk Measures.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child and Adolescent Psychosocial and Emotional Development","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University","funders":"","keywords":"Vulnerability (computing); Predictive power; Neighbourhood (mathematics); Population; Statistics; Demography; Psychology; Medicine; Computer science; Mathematics; Environmental health","score_opus":0.15488510897557917,"score_gpt":0.46105389775070854,"score_spread":0.3061687887751294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243664","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9867589,0.00009061567,0.0041676564,0.00071046624,0.0057366,0.000271483,0.00056648586,0.000023905011,0.0016739141],"genre_scores_gemma":[0.99120116,0.0000146312095,0.007342232,0.00026981626,0.00045203234,0.000016534112,0.00029899649,0.000007464559,0.0003971233],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975627,0.00014755916,0.0004285831,0.00045656518,0.0011860834,0.00021850874],"domain_scores_gemma":[0.99902946,0.00014410682,0.0003332599,0.0001417655,0.00024566593,0.00010575464],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004200631,0.000101994316,0.000100945486,0.00018320687,0.0023677961,0.00021457905,0.0008688878,0.000014235851,0.0004396825],"category_scores_gemma":[0.00064562494,0.00009654155,0.00003655848,0.00022175508,0.00010603723,0.0007557111,0.0005403891,0.00027389836,0.000004683856],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038067633,0.00030826565,0.5091103,0.0000038332937,0.00015177453,0.0000067855776,0.005808418,0.0021623592,0.0005320337,0.015574927,0.0022535205,0.46370712],"study_design_scores_gemma":[0.0014770533,0.000066042136,0.9596858,0.000027155542,0.000017318194,0.00021447793,0.0014529264,0.010883046,0.000008815425,0.011106067,0.014857858,0.00020341831],"about_ca_topic_score_codex":0.00039115327,"about_ca_topic_score_gemma":0.0000446819,"teacher_disagreement_score":0.46350372,"about_ca_system_score_codex":0.0003511084,"about_ca_system_score_gemma":0.00019837302,"threshold_uncertainty_score":0.998931},"labels":[],"label_agreement":null},{"id":"W4294243740","doi":"10.23889/ijpds.v7i3.1858","title":"Using routinely collected data to develop and evaluate a clinical tool for early identification of palliative care needs in long-term care: The RESPECT Project.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Frailty in Older Adults","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ottawa Hospital; University of Ottawa; Bruyère","funders":"","keywords":"Medicine; Minimum Data Set; Cohort; Long-term care; Risk assessment; Palliative care; Proportional hazards model; Cohort study; Gerontology; Logistic regression; Emergency medicine; Demography; Internal medicine; Nursing homes; Nursing","score_opus":0.32542797187420575,"score_gpt":0.5244270874010293,"score_spread":0.19899911552682353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243740","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9816894,0.0000943416,0.011898729,0.0013155651,0.0010880036,0.0016933391,0.002207989,0.000007718917,0.000004910161],"genre_scores_gemma":[0.987195,0.000014869597,0.010345196,0.00012603111,0.00017665008,0.0000445766,0.0020254897,0.000010967572,0.00006120184],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972788,0.00011296774,0.0009126052,0.0004203776,0.0011033424,0.00017191454],"domain_scores_gemma":[0.9964156,0.00030271863,0.0005205078,0.00059509836,0.0021097765,0.000056288798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032836755,0.00009176201,0.00017474471,0.00052523136,0.00040840695,0.0001845915,0.0016582442,0.000025645842,0.0000065017944],"category_scores_gemma":[0.007598547,0.00007513101,0.000027756565,0.0012448088,0.00011324645,0.0008198342,0.0010088586,0.00019948732,3.074441e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013275654,0.00008468105,0.96803033,0.000049871287,0.00007112335,0.0000064554238,0.006682439,0.0007577093,0.002597552,0.00024745511,0.0006001907,0.019544616],"study_design_scores_gemma":[0.0017792475,0.00020713311,0.9532042,0.00012005961,0.000056740075,0.000048016667,0.0013471899,0.042588927,0.00010889648,0.000057804144,0.00039447888,0.000087321714],"about_ca_topic_score_codex":0.0002962359,"about_ca_topic_score_gemma":0.000393754,"teacher_disagreement_score":0.041831218,"about_ca_system_score_codex":0.00052595936,"about_ca_system_score_gemma":0.0012248297,"threshold_uncertainty_score":0.90967196},"labels":[],"label_agreement":null},{"id":"W4294243752","doi":"10.23889/ijpds.v7i3.1826","title":"Impact of the COVID-19 pandemic on skin cancer diagnosis: A population-based study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University","funders":"","keywords":"Medicine; Pandemic; Skin cancer; Biopsy; Poisson regression; Cancer registry; Population; Cancer; Cohort; Cohort study; Melanoma; Dermatology; Coronavirus disease 2019 (COVID-19); Demography; Internal medicine; Disease; Environmental health; Infectious disease (medical specialty)","score_opus":0.2482335446101796,"score_gpt":0.550354455012218,"score_spread":0.3021209104020384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243752","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9865808,0.00003655199,0.00032803562,0.00914301,0.0015909723,0.0007422599,0.0015551698,0.000017405582,0.0000058181076],"genre_scores_gemma":[0.9954008,0.000013127422,0.00008521478,0.003818578,0.0002744794,0.000109853536,0.0002496381,0.000010743068,0.000037601276],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969966,0.00011086232,0.00049285614,0.00032789915,0.0018548396,0.00021693313],"domain_scores_gemma":[0.997917,0.00037581217,0.0005211075,0.0005266005,0.00038993955,0.00026955362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019249305,0.000111127825,0.00017466099,0.00047582135,0.00081963337,0.00008066684,0.0013045867,0.000022231785,0.00046745565],"category_scores_gemma":[0.0036238334,0.000075869895,0.00013509532,0.0006097431,0.000053918,0.00043152052,0.00028123744,0.00029399482,8.081466e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041015926,0.00031426147,0.96466535,0.0000098102555,0.000041434265,0.000004174599,0.00018592055,0.027978415,0.00004634248,0.000086656706,0.0017024598,0.004555029],"study_design_scores_gemma":[0.001659994,0.00050958025,0.9857349,0.00004198134,0.00003852555,0.000060532795,0.00008721212,0.008709062,0.0000050162,0.0002485221,0.0028282728,0.00007644465],"about_ca_topic_score_codex":0.015131221,"about_ca_topic_score_gemma":0.0016160641,"teacher_disagreement_score":0.02106952,"about_ca_system_score_codex":0.0030349006,"about_ca_system_score_gemma":0.0031783779,"threshold_uncertainty_score":0.9914271},"labels":[],"label_agreement":null},{"id":"W4294243772","doi":"10.23889/ijpds.v7i3.1832","title":"Quantifying intersecting structural racism in the youth criminal justice system: a whole-population linked administrative data study from Manitoba.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Memorial University of Newfoundland; First Nations Health and Social Secretariat of Manitoba; University of Manitoba","funders":"","keywords":"Criminal justice; Population; Residence; Demography; Economic Justice; Criminology; Racism; Geography; Political science; Sociology; Law","score_opus":0.3082029782714531,"score_gpt":0.4821870031112193,"score_spread":0.17398402483976622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243772","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98624974,0.00003345641,0.0008124869,0.0003703646,0.0097179795,0.0010074314,0.0014609031,0.00002866427,0.00031894684],"genre_scores_gemma":[0.9935978,0.000017132908,0.0010443329,0.000060050355,0.0018464533,0.000008030223,0.003380768,0.000010003868,0.000035448913],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9951658,0.0008404544,0.0007748033,0.00063227664,0.002190858,0.00039578293],"domain_scores_gemma":[0.9975473,0.0004635624,0.0007502483,0.0006761383,0.00045561744,0.000107129104],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.008697104,0.0001422134,0.00016235297,0.0003980426,0.013229637,0.0010868425,0.0054269196,0.0000392454,0.000030203999],"category_scores_gemma":[0.0003590229,0.000112923655,0.000035273428,0.00059822924,0.00014387713,0.0037727426,0.00012621265,0.0004961677,0.000003237726],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024543033,0.00030962986,0.086222805,0.00002540407,0.000052892457,0.00003641277,0.874413,0.0010981257,0.000010091574,0.035098404,0.00006197631,0.0024258299],"study_design_scores_gemma":[0.0005226475,0.0001036523,0.1715645,0.00005582158,0.00015158852,0.000056540863,0.8045357,0.019631913,5.957166e-7,0.00046829376,0.0027254666,0.00018329291],"about_ca_topic_score_codex":0.22564678,"about_ca_topic_score_gemma":0.6280599,"teacher_disagreement_score":0.40241313,"about_ca_system_score_codex":0.0012149476,"about_ca_system_score_gemma":0.002907811,"threshold_uncertainty_score":0.9999542},"labels":[],"label_agreement":null},{"id":"W4294243777","doi":"10.23889/ijpds.v7i3.1955","title":"Better decision making practices and processes.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transparency (behavior); Accountability; Confidentiality; Decision engineering; Decision-making; Business decision mapping; Decision analysis; Process (computing); Data sharing; R-CAST; Management science; Business; Process management; Decision support system; Computer science; Political science; Medicine; Engineering; Computer security; Economics; Data mining","score_opus":0.6436834655748153,"score_gpt":0.6863148571301672,"score_spread":0.042631391555351894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243777","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94800526,0.00021630558,0.017911952,0.029919539,0.0028254273,0.00037643686,0.00021138467,0.000022665838,0.00051102904],"genre_scores_gemma":[0.96123236,0.00012235626,0.036575418,0.0014438486,0.00037436685,0.000008562216,0.00007380401,0.0000068221802,0.00016247708],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9965222,0.000026195507,0.0003381348,0.00034388865,0.002620092,0.00014947407],"domain_scores_gemma":[0.9944547,0.003247163,0.0004991999,0.0003313809,0.0013522403,0.00011533571],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0075984197,0.000049967693,0.00007815998,0.0002817972,0.00069974957,0.00035248348,0.0012475007,0.0000272828,0.000180355],"category_scores_gemma":[0.060921904,0.000042542884,0.000018479908,0.0003085365,0.00015024362,0.0015832619,0.0012895722,0.0007104622,0.00000255217],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019442796,0.00039353874,0.6176966,0.00013000387,0.000097492964,0.00014339344,0.00040345453,0.0004605785,0.0020643815,0.01870332,0.0058026933,0.35216027],"study_design_scores_gemma":[0.003025876,0.00077806663,0.4922092,0.000671823,0.00008229056,0.004332749,0.0007249788,0.0810564,0.00015092123,0.2769001,0.13972336,0.00034422777],"about_ca_topic_score_codex":0.000022765837,"about_ca_topic_score_gemma":0.000042101154,"teacher_disagreement_score":0.35181606,"about_ca_system_score_codex":0.00016670456,"about_ca_system_score_gemma":0.00067444536,"threshold_uncertainty_score":0.94698834},"labels":[],"label_agreement":null},{"id":"W4294243784","doi":"10.23889/ijpds.v7i3.1825","title":"A Decolonizing Approach in Population Health Research: Examining the Association between the federal maternal evacuation policy on Maternal and Child outcomes in First Nation (FN) Communities in Manitoba.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Winnipeg; University of Manitoba; Manitoba Health; First Nations Health and Social Secretariat of Manitoba","funders":"","keywords":"Indigenous; Population; Metis; Breastfeeding; Odds; Medicine; Population health; Harm; Demography; Gerontology; Psychology; Sociology; Environmental health; Pediatrics; Social psychology","score_opus":0.294213638897651,"score_gpt":0.45778134208474547,"score_spread":0.16356770318709446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9854974,0.00003840568,0.00006992769,0.01185602,0.0009273844,0.0009387862,0.00008706818,0.000011430284,0.0005735821],"genre_scores_gemma":[0.9979864,0.00046112412,0.00019950213,0.00023759907,0.00059710105,0.000037189544,0.0003816899,0.000010323864,0.00008908408],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99462867,0.0015834421,0.00073104684,0.00028491154,0.0022137284,0.00055818225],"domain_scores_gemma":[0.9977577,0.0010438517,0.00059569965,0.00023750176,0.0002870069,0.00007829439],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.024945676,0.000111803456,0.00016589164,0.001357403,0.012413235,0.00088716426,0.0015953191,0.00005540357,0.00000929735],"category_scores_gemma":[0.00040113623,0.00008371061,0.000023316403,0.00097308645,0.00015722589,0.0017360416,0.00007661719,0.0007456771,0.0000010161965],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003117366,0.000059667156,0.92961836,0.000006057118,0.000006965702,4.946524e-7,0.036055766,0.0024343736,9.708965e-8,0.030204805,0.0000145982485,0.001567662],"study_design_scores_gemma":[0.00045323768,0.00005437519,0.97626257,0.00007216405,0.0000017202752,0.000009383106,0.010108407,0.0043172506,5.041708e-7,0.0040835273,0.0045542186,0.00008262985],"about_ca_topic_score_codex":0.50622773,"about_ca_topic_score_gemma":0.8184224,"teacher_disagreement_score":0.31219462,"about_ca_system_score_codex":0.005955319,"about_ca_system_score_gemma":0.0023304045,"threshold_uncertainty_score":0.99786067},"labels":[],"label_agreement":null},{"id":"W4294243789","doi":"10.23889/ijpds.v7i3.1918","title":"Costs of missed work among employed people with inflammatory bowel disease: a cross-sectional population-representative study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Health Care Issues","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hospital for Sick Children; University of Ottawa; University of Calgary; SickKids Foundation; University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Medicine; Inflammatory bowel disease; Population; Logistic regression; Odds ratio; Cross-sectional study; Odds; Disease; Demography; Environmental health; Internal medicine; Pathology","score_opus":0.09691964134887923,"score_gpt":0.5049495114179691,"score_spread":0.40802987006908986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294243789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9918565,0.000036705565,0.0006346302,0.00046920867,0.0040516555,0.0015598382,0.0012951691,0.000047796657,0.000048503276],"genre_scores_gemma":[0.9968789,0.0000037650948,0.0007594887,0.0001734694,0.00038884635,0.00020108868,0.0012760006,0.000023524852,0.00029492125],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9944425,0.0004185685,0.0011711129,0.00060364534,0.0029266796,0.00043744463],"domain_scores_gemma":[0.99524504,0.00056140346,0.001309273,0.0005935747,0.0019544757,0.00033620416],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0032485365,0.00017074562,0.0002175386,0.0005110767,0.0029093516,0.00013440596,0.0020649007,0.00003973862,0.00041881064],"category_scores_gemma":[0.0015935514,0.00015616264,0.00006064005,0.0007820726,0.00018262229,0.0021660642,0.0009671745,0.0005366974,0.000010058982],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012197252,0.00017325356,0.98550326,0.000018181227,0.000047127378,0.000012125696,0.0010662298,0.008930831,0.000009810659,0.0008141353,0.00214667,0.000058662128],"study_design_scores_gemma":[0.0015162214,0.00013708018,0.9920389,0.00009257698,0.000018298093,0.000010407812,0.0020895016,0.0030310103,8.758772e-7,0.00043474056,0.00047751723,0.00015286593],"about_ca_topic_score_codex":0.002975532,"about_ca_topic_score_gemma":0.0014160097,"teacher_disagreement_score":0.006535656,"about_ca_system_score_codex":0.001350631,"about_ca_system_score_gemma":0.0009643907,"threshold_uncertainty_score":0.9983887},"labels":[],"label_agreement":null},{"id":"W4301605997","doi":"10.23889/ijpds.v7i1.1757","title":"A scoping review of preprocessing methods for unstructured text data to assess data quality","year":2022,"lang":"en","type":"review","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; George & Fay Yee Centre for Healthcare Innovation; Manitoba Health","funders":"Canada Research Chairs","keywords":"Computer science; Preprocessor; Punctuation; Data quality; Data pre-processing; Stop words; Information retrieval; Lexical analysis; Natural language processing; Artificial intelligence; Data mining","score_opus":0.9239911994930267,"score_gpt":0.7624971008446532,"score_spread":0.1614940986483735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301605997","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.775133e-7,0.50871915,0.45906195,0.00053468277,0.003809113,0.001991975,0.0258214,0.000012734808,0.00004884132],"genre_scores_gemma":[7.113046e-7,0.6736616,0.2973722,0.0004914062,0.0003421187,0.000062115716,0.027946467,0.000019748732,0.00010366798],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9858254,0.0013752916,0.004651135,0.0027198945,0.005014746,0.0004135255],"domain_scores_gemma":[0.9694701,0.008737557,0.0073152576,0.012089778,0.002060535,0.00032680912],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["metaresearch","open_science"],"category_scores_codex":[0.119293615,0.0003425022,0.00166487,0.0011385233,0.0007887261,0.0021248998,0.0544372,0.00007620063,0.00041845653],"category_scores_gemma":[0.15512058,0.0002622833,0.00022184687,0.002136638,0.0001927214,0.009437866,0.025450964,0.0003545998,0.0000074438117],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001638609,0.00003557527,0.0000031983682,0.015165743,0.00007216633,7.1137333e-7,0.000015818116,0.000017344075,9.618203e-7,0.0012809657,0.014333921,0.9690572],"study_design_scores_gemma":[0.00014764289,0.00002282537,0.000014626487,0.06427237,0.00024886287,0.000049237944,0.000057191693,0.003803544,4.46795e-7,0.0025340237,0.9285659,0.0002832889],"about_ca_topic_score_codex":0.000085950196,"about_ca_topic_score_gemma":0.0000698519,"teacher_disagreement_score":0.9687739,"about_ca_system_score_codex":0.00027663723,"about_ca_system_score_gemma":0.0027547234,"threshold_uncertainty_score":0.99998295},"labels":[],"label_agreement":null},{"id":"W4304942817","doi":"10.23889/ijpds.v7i4.1763","title":"How to analyze and link patient experience surveys with administrative data to drive health service improvement -- examples from Alberta, Canada","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Patient Satisfaction in Healthcare","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Variety (cybernetics); Quality (philosophy); Patient experience; Service (business); Health care; Protocol (science); Survey data collection; Work (physics); Isolation (microbiology); Data collection; Quality management; Medicine; Nursing; Psychology; Medical emergency; Business; Computer science; Alternative medicine; Engineering; Marketing; Political science","score_opus":0.22686950187736224,"score_gpt":0.47656323354710156,"score_spread":0.24969373166973932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4304942817","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8929594,0.000022586837,0.011362804,0.07052225,0.0038162714,0.0015642575,0.019724267,0.000015426564,0.000012709328],"genre_scores_gemma":[0.9763837,0.00000828176,0.009347434,0.00903886,0.00027111583,0.00020519391,0.004633814,0.000015995709,0.00009562165],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99543166,0.0004828402,0.0007489807,0.00091669266,0.0019301295,0.0004897099],"domain_scores_gemma":[0.9957604,0.00072730886,0.0008191167,0.0009772333,0.0010524467,0.0006634908],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0019340881,0.00017310446,0.00022116835,0.0002601892,0.0028583065,0.00018254944,0.0023971586,0.000024634424,0.00014370341],"category_scores_gemma":[0.0012908261,0.00015522125,0.000010359358,0.0006218332,0.000043867753,0.0017333537,0.0023266356,0.00040692327,0.0000021949086],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032029932,0.00004411431,0.91327834,0.000031075102,0.00007473429,0.000011223416,0.014192465,0.0017638531,0.00023373784,0.000477257,0.012426984,0.05714589],"study_design_scores_gemma":[0.00062808924,0.0006172503,0.8829924,0.00014569575,0.00000935849,0.000019769923,0.021551775,0.0088509675,0.000021361739,0.00009936316,0.084767446,0.0002965182],"about_ca_topic_score_codex":0.838883,"about_ca_topic_score_gemma":0.94109577,"teacher_disagreement_score":0.10221274,"about_ca_system_score_codex":0.0018286377,"about_ca_system_score_gemma":0.0041019227,"threshold_uncertainty_score":0.99843985},"labels":[],"label_agreement":null},{"id":"W4306789942","doi":"10.23889/ijpds.v7i4.1759","title":"Representativeness of survey participants in relation to mental disorders: a linkage between national registers and a population-representative survey","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Lundbeckfonden","keywords":"Representativeness heuristic; Linkage (software); Relation (database); Population; Psychology; Record linkage; Medicine; Environmental health; Computer science; Data mining; Social psychology; Genetics; Biology","score_opus":0.5850050008153506,"score_gpt":0.5850696942076199,"score_spread":0.00006469339226933268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306789942","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919427,0.000019416593,0.0027581267,0.001094074,0.0012680817,0.00045712004,0.002396989,0.000008414306,0.0000550904],"genre_scores_gemma":[0.99607134,0.000021286649,0.00196348,0.00006668068,0.00008708389,0.00002817587,0.0016501956,0.000007505136,0.000104236744],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98890305,0.007876519,0.00067639205,0.00050743564,0.0017361745,0.0003004074],"domain_scores_gemma":[0.99074715,0.007854765,0.00048518542,0.00020355318,0.00056438945,0.00014496353],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.067362346,0.00009409929,0.00019148552,0.0007024994,0.0009832139,0.00012287161,0.0011632564,0.00003976543,0.000056883975],"category_scores_gemma":[0.044667523,0.00010467577,0.000031223837,0.0010908829,0.00030504467,0.0016961218,0.00053584465,0.00019337283,8.996916e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013748034,0.000054431774,0.9901475,0.0000013251579,0.00002382845,9.1637713e-7,0.004478661,0.0013619064,0.000063381885,0.0006685194,0.00023361018,0.0015911224],"study_design_scores_gemma":[0.0005599608,0.000051397208,0.9935148,0.000014269168,0.0000049437967,0.0000022954662,0.0013622312,0.0012857517,0.000010850859,0.002639255,0.00044494637,0.00010929969],"about_ca_topic_score_codex":0.04140707,"about_ca_topic_score_gemma":0.031843603,"teacher_disagreement_score":0.022694822,"about_ca_system_score_codex":0.00041248137,"about_ca_system_score_gemma":0.00042043376,"threshold_uncertainty_score":0.98582274},"labels":[],"label_agreement":null},{"id":"W4307276157","doi":"10.23889/ijpds.v7i1.1756","title":"Describing a complex primary health care population to support future decision support initiatives","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Access Alliance Multicultural Health and Community Services; Western University","funders":"Canadian Institutes of Health Research","keywords":"Clinical decision support system; Health care; Decision support system; Population; Population health; Stakeholder; Family medicine; Nursing; Medicine; Community health; Public health; Environmental health; Data mining; Computer science","score_opus":0.16785233296656177,"score_gpt":0.45440470481849055,"score_spread":0.2865523718519288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307276157","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8027172,0.00047441307,0.0845988,0.061155908,0.026253548,0.0061046295,0.010453173,0.00043313464,0.0078092017],"genre_scores_gemma":[0.9587047,0.000026106318,0.019928906,0.0054302267,0.0008090356,0.000027608607,0.014982717,0.000019054152,0.0000716351],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9964394,0.00004486622,0.00060671906,0.000511503,0.0020761483,0.0003213496],"domain_scores_gemma":[0.99834216,0.000047148653,0.00037032212,0.00044704237,0.0004559546,0.00033736313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012891688,0.00014167599,0.00020723935,0.000734751,0.001037498,0.00033060944,0.0012197255,0.000017293361,0.0008810081],"category_scores_gemma":[0.00033096626,0.00014012957,0.00007530602,0.0005082885,0.000050396473,0.002199682,0.0009895172,0.00019808795,0.000008752875],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022989635,0.0005840084,0.119220614,0.00015505796,0.00020055471,0.00017879558,0.0037199,0.008983493,0.00060248614,0.020462234,0.1986484,0.6449455],"study_design_scores_gemma":[0.002183646,0.00085677335,0.85545224,0.00009394901,0.000048272388,0.0004069255,0.0040281024,0.003795672,0.000005142803,0.000617473,0.13225123,0.00026055644],"about_ca_topic_score_codex":0.000118681586,"about_ca_topic_score_gemma":0.00007048714,"teacher_disagreement_score":0.7362316,"about_ca_system_score_codex":0.0020955224,"about_ca_system_score_gemma":0.0011643426,"threshold_uncertainty_score":0.9646421},"labels":[],"label_agreement":null},{"id":"W4307300331","doi":"10.23889/ijpds.v7i1.1708","title":"Using Linked Data to Identify Pathways of Reporting Overdose Events in British Columbia, 2015 - 2017","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa; University of British Columbia; BC Centre for Disease Control; Public Health Agency of Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Health, British Columbia","keywords":"Medicine; Drug overdose; Emergency department; Cohort; Health care; Medical emergency; Cohort study; Emergency medicine; Public health; Opioid overdose; Family medicine; Poison control; Psychiatry; Nursing; Opioid","score_opus":0.263308392816434,"score_gpt":0.48497593343779505,"score_spread":0.22166754062136107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307300331","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942167,0.000083857914,0.0011779072,0.00035613918,0.0018334909,0.00043566892,0.0018752877,0.000008554791,0.000012405436],"genre_scores_gemma":[0.9848497,0.000020585177,0.012225841,0.00011902496,0.00012509341,0.000008768429,0.0025612593,0.000010916519,0.00007883057],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967897,0.000034364675,0.0010748276,0.00045955615,0.0014460434,0.0001954952],"domain_scores_gemma":[0.99756306,0.00003616776,0.0011430023,0.0007465553,0.0003954477,0.00011575639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029926877,0.00006123012,0.00018460194,0.000278129,0.00032264134,0.00018889611,0.0016848992,0.000018278828,0.00009622383],"category_scores_gemma":[0.003086825,0.000090889516,0.000036920872,0.00040271212,0.000034123892,0.0015491743,0.0017466854,0.00016031353,0.000001294075],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005124929,0.00030572142,0.9858003,0.00001343807,0.000034487646,0.0001144001,0.00014177083,0.0012814504,0.005419828,0.000012079544,0.00230111,0.0045241094],"study_design_scores_gemma":[0.0010349142,0.00007177197,0.9562704,0.00019896199,0.000027940809,0.0008621309,0.00031878744,0.039767597,0.0000136480785,0.00036455743,0.0009837731,0.00008549754],"about_ca_topic_score_codex":0.01909449,"about_ca_topic_score_gemma":0.005738257,"teacher_disagreement_score":0.038486145,"about_ca_system_score_codex":0.00051390566,"about_ca_system_score_gemma":0.0005784063,"threshold_uncertainty_score":0.9874374},"labels":[],"label_agreement":null},{"id":"W4309836268","doi":"10.23889/ijpds.v7i4.1755","title":"Validating a novel deterministic privacy-preserving record linkage between administrative &amp; clinical data: applications in stroke research","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ted Rogers Centre for Heart Research; Indoc Research; University Health Network; University of Toronto; Health Sciences Centre; Ontario Brain Institute; Heart and Stroke Foundation; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research; University of Toronto; Ontario Ministry of Health and Long-Term Care; Government of Ontario; Department of Medicine, University of Toronto; Ontario Brain Institute; Heart and Stroke Foundation of Canada","keywords":"Record linkage; Linkage (software); Computer science; Medical record; Stroke (engine); Data science; Medicine; Engineering; Genetics; Gene; Biology; Environmental health; Internal medicine","score_opus":0.8808373577486144,"score_gpt":0.6882838280011057,"score_spread":0.19255352974750872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309836268","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34877247,0.0000331565,0.609324,0.007706007,0.004499306,0.0017497698,0.026847279,0.000047132384,0.0010208917],"genre_scores_gemma":[0.93915176,0.000017179336,0.0536749,0.00018791227,0.00084984757,0.00007649742,0.0051920763,0.000013463533,0.0008363769],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.98899704,0.0008802238,0.002225126,0.0014706752,0.005942395,0.00048451428],"domain_scores_gemma":[0.9836115,0.009209928,0.001374432,0.004045782,0.0014501251,0.00030819935],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["metaresearch","open_science"],"category_scores_codex":[0.074597135,0.00014139549,0.00029191258,0.0012901521,0.00189623,0.002310759,0.024463499,0.000047594265,0.00025208713],"category_scores_gemma":[0.049950123,0.00012951242,0.00006958383,0.0017633335,0.00035570553,0.0055440464,0.018923897,0.0009803541,0.000033435605],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025853037,0.0011016782,0.6440929,0.00001864894,0.00011922713,0.000026135855,0.0010894261,0.0016419396,0.0004156381,0.027719803,0.036165755,0.28735027],"study_design_scores_gemma":[0.000968633,0.00015453536,0.18700662,0.0000428254,0.000021808624,0.000031389394,0.003191502,0.058750357,0.0000073467636,0.03917782,0.7103605,0.000286627],"about_ca_topic_score_codex":0.0003552016,"about_ca_topic_score_gemma":0.00075649266,"teacher_disagreement_score":0.67419475,"about_ca_system_score_codex":0.00037635464,"about_ca_system_score_gemma":0.00072272914,"threshold_uncertainty_score":0.9994032},"labels":[],"label_agreement":null},{"id":"W4318480423","doi":"10.23889/ijpds.v5i3.2114","title":"Understanding how to build a social licence for using novel linked datasets for planning and research in Kent, Surrey and Sussex: results of deliberative focus groups.","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Engineering and Physical Sciences Research Council; Public Health Research Programme; Department of Health and Social Care; National Institute for Health and Care Research","keywords":"Safeguarding; Transparency (behavior); Focus group; Accountability; Audit; Public relations; Public health; Population; Open data; Information governance; Business; Medicine; Political science; Nursing; Computer science; Information system; World Wide Web; Environmental health; Computer security; Accounting","score_opus":0.6058132047506097,"score_gpt":0.5566826608196977,"score_spread":0.049130543930911985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318480423","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5835102,0.000028954422,0.39173496,0.010522061,0.00063122483,0.0009371306,0.012583875,0.00001449375,0.000037072456],"genre_scores_gemma":[0.981913,0.000019480884,0.01671492,0.000024386492,0.00030833556,0.000010219919,0.0009894881,0.000005958287,0.000014249722],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980412,0.00006666951,0.00033863002,0.00039706085,0.00081777136,0.0003386353],"domain_scores_gemma":[0.9980095,0.0011308022,0.00022673914,0.00012177162,0.00039985063,0.000111323534],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008741429,0.000069594906,0.00013612791,0.0008424735,0.0015129579,0.0007856421,0.00087240414,0.000031472002,7.164013e-7],"category_scores_gemma":[0.004317416,0.00006785112,0.000025226875,0.00085727614,0.00029703087,0.0022760907,0.00044426756,0.00010665215,7.796414e-8],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029053085,0.0003254219,0.09463923,0.00014936701,0.00026331414,0.000016225174,0.08319309,0.0051613664,0.042786296,0.7116221,0.014425487,0.04451277],"study_design_scores_gemma":[0.0056302426,0.00032517203,0.089595065,0.0011609864,0.00006588735,0.000020075642,0.06311094,0.7426368,0.0002575583,0.07974648,0.016767249,0.000683533],"about_ca_topic_score_codex":0.00078490545,"about_ca_topic_score_gemma":0.0025117109,"teacher_disagreement_score":0.73747545,"about_ca_system_score_codex":0.00020327796,"about_ca_system_score_gemma":0.00020167932,"threshold_uncertainty_score":0.9997869},"labels":[],"label_agreement":null},{"id":"W4318992451","doi":"10.23889/ijpds.v8i1.1843","title":"Student Achievement Trajectories in Ontario: Creating and validating a province-wide, multi-cohort and longitudinal database","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Christian Studies; Memorial University of Newfoundland","funders":"Government of Ontario","keywords":"Linkage (software); Tracking (education); Demographics; Cohort; Identification (biology); Population; Psychological intervention; Scale (ratio); Longitudinal study; Computer science; Database; Psychology; Geography; Demography; Medicine; Environmental health; Pedagogy","score_opus":0.11394359904723726,"score_gpt":0.42159547494806465,"score_spread":0.3076518759008274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318992451","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99602234,0.00002268532,0.0008049483,0.0013477496,0.0011993899,0.00034044392,0.00004090404,0.000024857303,0.0001966928],"genre_scores_gemma":[0.9862952,0.00009738207,0.012520018,0.0000892647,0.00015042357,0.00001371705,0.00021142686,0.000005341658,0.00061721174],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99800783,0.000047534864,0.0003690744,0.00037764662,0.00094347296,0.000254442],"domain_scores_gemma":[0.99911904,0.00018534437,0.00018371257,0.00014009632,0.00022456591,0.00014726346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003897958,0.00008547928,0.000096403695,0.00035182294,0.0009817906,0.0008414767,0.0006535761,0.000023193748,0.000024869258],"category_scores_gemma":[0.0014986136,0.00008222026,0.000012989992,0.0003142991,0.0001631011,0.0023796738,0.00037527407,0.00014506163,0.0000021678745],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000071482045,0.000040672636,0.98756415,0.0000022079187,0.000010936342,0.000003925764,0.0069160433,0.000044013865,0.000029331963,0.0029862132,0.00009670461,0.0022986657],"study_design_scores_gemma":[0.00035311555,0.000013598102,0.9923599,0.00006425838,0.0000056329845,0.000006182879,0.0039764037,0.0008055804,0.0000072414896,0.0002524232,0.0020564275,0.00009927583],"about_ca_topic_score_codex":0.0570298,"about_ca_topic_score_gemma":0.2894066,"teacher_disagreement_score":0.2323768,"about_ca_system_score_codex":0.00044293088,"about_ca_system_score_gemma":0.0010348436,"threshold_uncertainty_score":0.9492495},"labels":[],"label_agreement":null},{"id":"W4321493419","doi":"10.23889/ijpds.v8i1.2125","title":"Everybody’s talking about equity, but is anyone really listening?: The Case for Better Data-Driven Learning in Health Systems","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Trillium Health Centre","funders":"","keywords":"Health care; Public relations; Health equity; Equity (law); Data collection; Wonder; Data quality; Psychological intervention; Internet privacy; Data science; Political science; Medicine; Business; Psychology; Computer science; Sociology; Nursing; Service (business); Marketing","score_opus":0.2440635834691358,"score_gpt":0.5481205311034185,"score_spread":0.3040569476342827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321493419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53650236,0.0010957927,0.058502864,0.3348279,0.044308234,0.0073819044,0.015556637,0.0005084453,0.0013158572],"genre_scores_gemma":[0.96294427,0.00053086644,0.0047519277,0.019603427,0.0033969257,0.00014720761,0.005421925,0.00005249111,0.0031509825],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9960274,0.00030093256,0.00133616,0.0005786814,0.0009833388,0.0007734825],"domain_scores_gemma":[0.9959516,0.0013360672,0.0010725188,0.00079227274,0.00065427274,0.00019329476],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.012491033,0.00014749433,0.00028172455,0.0005539955,0.0030782868,0.00035508242,0.0032769525,0.00008255593,0.00003488775],"category_scores_gemma":[0.0024940704,0.000112711044,0.00005120953,0.00054882123,0.00009078302,0.0026595702,0.0024857952,0.0007101618,0.000029082204],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037418967,0.00008407614,0.3281002,0.0010627937,0.00013244274,0.00036844867,0.0056139445,0.00813586,0.0002413998,0.011507225,0.534593,0.109786436],"study_design_scores_gemma":[0.0017582391,0.000118047494,0.13502692,0.0008791021,0.000021655036,0.0005987776,0.0029695558,0.5067788,9.073335e-7,0.0018058374,0.34975153,0.00029064267],"about_ca_topic_score_codex":0.007247568,"about_ca_topic_score_gemma":0.0030930946,"teacher_disagreement_score":0.49864292,"about_ca_system_score_codex":0.0010905254,"about_ca_system_score_gemma":0.0021875324,"threshold_uncertainty_score":0.99936324},"labels":[],"label_agreement":null},{"id":"W4362553806","doi":"10.23889/ijpds.v7i4.1761","title":"Association between neighbourhood composition, kindergarten educator-reported distance learning barriers, and return to school concerns during the first wave of the COVID-19 pandemic in Ontario, Canada","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University","funders":"","keywords":"Neighbourhood (mathematics); Poisson regression; Mental health; Census; Coronavirus disease 2019 (COVID-19); Pandemic; Psychology; Distance education; Association (psychology); Medical education; Medicine; Mathematics education; Environmental health; Population","score_opus":0.09962340216359046,"score_gpt":0.41534684976832764,"score_spread":0.3157234476047372,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362553806","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9837992,0.000013826984,0.00028319046,0.013423803,0.0018311136,0.00030066777,0.00029611817,0.000011141576,0.000040896357],"genre_scores_gemma":[0.9979979,0.000008040774,0.000021544509,0.0010258937,0.00018716483,0.000012557543,0.00015495592,0.000006046022,0.00058590097],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982033,0.000079258636,0.00046244435,0.00028189723,0.0007318534,0.00024129487],"domain_scores_gemma":[0.99849117,0.00035316774,0.00050661707,0.00024249518,0.0001740695,0.00023248506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001708221,0.000079949576,0.00011182228,0.00014859594,0.0007655144,0.00010084073,0.0007287173,0.000035931647,0.00015750187],"category_scores_gemma":[0.0015545784,0.00006028668,0.000023527435,0.00042289804,0.000058374702,0.00037668366,0.00022919125,0.0003208068,0.000001137197],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041990043,0.0000057641123,0.99532795,0.0000058641967,0.000031191925,0.0000033879062,0.0011513736,0.00047109328,0.000061023788,0.0001600855,0.002567586,0.00017271061],"study_design_scores_gemma":[0.0004975301,0.000014375522,0.977593,0.0000396536,0.0000128211495,0.00003914367,0.0007267032,0.0004517131,0.0000073877427,0.00023826887,0.020312568,0.000066833716],"about_ca_topic_score_codex":0.7521155,"about_ca_topic_score_gemma":0.9476887,"teacher_disagreement_score":0.19557317,"about_ca_system_score_codex":0.0048963507,"about_ca_system_score_gemma":0.0029616486,"threshold_uncertainty_score":0.99892366},"labels":[],"label_agreement":null},{"id":"W4381434415","doi":"10.23889/ijpds.v8i1.2134","title":"Color Coded Health Data: Factors related to willingness to share health information in South Asian community members in Canada","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Ethnic group; General partnership; Health information; Qualitative research; Population; Information sharing; Psychology; Public relations; Business; Environmental health; Medicine; Political science; Health care; Sociology; Computer science; World Wide Web","score_opus":0.2083858681817263,"score_gpt":0.523515959542217,"score_spread":0.31513009136049064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381434415","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96379495,0.000004912283,0.0020769082,0.019157004,0.0041743345,0.0017898472,0.008861605,0.00005163594,0.00008878582],"genre_scores_gemma":[0.9722827,0.00001071818,0.0018208643,0.01061237,0.000056421362,0.00003893603,0.015135877,0.000009086371,0.000032996668],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99407256,0.000605414,0.003005181,0.00032193656,0.0012365032,0.00075838825],"domain_scores_gemma":[0.99604416,0.00042335544,0.0012603615,0.00091881555,0.00071892625,0.0006343611],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.015759232,0.00015368174,0.00031502132,0.0010815527,0.0017557975,0.00018493863,0.0033120033,0.00006350237,0.000084828425],"category_scores_gemma":[0.006234054,0.00014102583,0.000017362963,0.0023007386,0.00003072906,0.010048044,0.001184516,0.00096030656,0.00004874233],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00024431766,0.00004333605,0.88412386,0.00021625016,0.000008666576,0.0000012197477,0.0556031,0.016186727,0.0000015348162,0.0005623897,0.023099396,0.019909225],"study_design_scores_gemma":[0.0006528252,0.0000415717,0.83616877,0.00042738198,6.917431e-7,0.0000016538872,0.02012748,0.11226109,4.6975705e-7,0.00013266377,0.030058827,0.00012660332],"about_ca_topic_score_codex":0.67297083,"about_ca_topic_score_gemma":0.8593423,"teacher_disagreement_score":0.18637143,"about_ca_system_score_codex":0.0048502134,"about_ca_system_score_gemma":0.009654665,"threshold_uncertainty_score":0.9995438},"labels":[],"label_agreement":null},{"id":"W4385810620","doi":"10.23889/ijpds.v8i1.2152","title":"Correlates of child mental health and substance use related emergency department visits in Ontario: A linked population survey and administrative health data study","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Children’s Health Research Institute; McMaster University; Lawson Health Research Institute; Western University","funders":"Hamilton Health Sciences Foundation; Ontario Ministry of Health and Long-Term Care; Children's Health Research Institute; Canadian Institutes of Health Research; Hamilton Health Sciences","keywords":"Medicine; Mental health; Emergency department; Population; Poisson regression; Substance abuse; Suicidal ideation; Family medicine; Psychiatry; Suicide prevention; Poison control; Environmental health","score_opus":0.18181521538396236,"score_gpt":0.4521289168207955,"score_spread":0.2703137014368331,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385810620","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99349463,0.00050019746,0.000040397903,0.0022687202,0.0012139599,0.0007617452,0.0017026174,0.000012994265,0.0000047376393],"genre_scores_gemma":[0.98703647,0.0017101167,0.00034178462,0.00007136119,0.000027330603,0.0000044711555,0.010739249,0.0000071970067,0.000061994724],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977455,0.00009511852,0.00084729487,0.00046616117,0.00064226124,0.00020366075],"domain_scores_gemma":[0.99867857,0.00007726909,0.00050295674,0.0003174473,0.00026985875,0.00015387332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025581957,0.000117269985,0.00025996155,0.000322776,0.0003777244,0.00004757887,0.00040412674,0.000024262124,0.0000101422465],"category_scores_gemma":[0.00081135816,0.00010356734,0.000016745103,0.00048308267,0.000060524202,0.0015137915,0.00031162176,0.00018697702,4.4349622e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020255671,0.00013656882,0.9946389,0.0000102957765,0.00006240122,0.000004076484,0.0019940524,0.000017669521,0.0000074642903,0.00011950502,0.0012157292,0.0015907421],"study_design_scores_gemma":[0.0010365221,0.0004313269,0.99298686,0.00016039566,0.000009240592,0.0000473132,0.0007783578,0.004170922,7.467601e-7,0.00011879651,0.00018184214,0.00007769613],"about_ca_topic_score_codex":0.024251334,"about_ca_topic_score_gemma":0.2888339,"teacher_disagreement_score":0.26458254,"about_ca_system_score_codex":0.00022996482,"about_ca_system_score_gemma":0.00028102237,"threshold_uncertainty_score":0.9822463},"labels":[],"label_agreement":null},{"id":"W4386751691","doi":"10.23889/ijpds.v8i2.2232","title":"Housing tenure and hospital admissions for acute lower respiratory tract infections in children less than 2 years: A Scottish birth cohort (2010-2012)","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"Economic and Social Research Council; Medical Research Council","keywords":"Medicine; Cohort; Bronchiolitis; Odds ratio; Odds; Pediatrics; Bronchitis; Socioeconomic status; Respiratory tract infections; Pneumonia; Demography; Cohort study; Logistic regression; Population; Environmental health; Internal medicine; Respiratory system","score_opus":0.06086653689874809,"score_gpt":0.4247809743777338,"score_spread":0.3639144374789857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386751691","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9904593,0.000053846576,0.0005311255,0.0042912597,0.003376262,0.000507425,0.00070867594,0.000041446685,0.00003061866],"genre_scores_gemma":[0.997549,0.00031599734,0.00061981915,0.00040619317,0.00068669097,0.000023323013,0.00015204385,0.000011281114,0.00023564084],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99832904,0.000041729883,0.00032308127,0.00030166173,0.0006343292,0.00037014054],"domain_scores_gemma":[0.9989716,0.0001707169,0.0001778961,0.00016486492,0.00024406628,0.00027087296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00227391,0.000079131394,0.000118531214,0.0003787088,0.0010147705,0.00054559775,0.000645027,0.00006304085,0.000027709504],"category_scores_gemma":[0.00190389,0.000077071796,0.000044982287,0.0004968321,0.0001614638,0.002769922,0.00015143279,0.00015418915,0.0000029185032],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010841594,0.000059081227,0.988665,0.0000023569298,0.000017687738,0.000003634797,0.0002860589,0.0000490972,0.000006306155,0.0022415123,0.0034537541,0.0052046753],"study_design_scores_gemma":[0.00037051042,0.000044404736,0.98104924,0.000066805034,0.00001184565,0.000011376393,0.00031550022,0.0006779065,8.034369e-7,0.0011288836,0.01621753,0.00010520188],"about_ca_topic_score_codex":0.002273061,"about_ca_topic_score_gemma":0.0033879157,"teacher_disagreement_score":0.012763775,"about_ca_system_score_codex":0.00019158964,"about_ca_system_score_gemma":0.0006562632,"threshold_uncertainty_score":0.7804897},"labels":[],"label_agreement":null},{"id":"W4386751706","doi":"10.23889/ijpds.v8i2.2213","title":"The employment, retention and exit of publicly employed nurses in New Brunswick, Canada: An analysis using linked administrative data","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Credential; Earnings; Licensure; Government (linguistics); Graduation (instrument); Descriptive statistics; Retraining; Immigration; Credentialing; Business; Certification; Demographic economics; Nursing; Psychology; Medicine; Political science; Economics; Accounting; Management","score_opus":0.36464290862423726,"score_gpt":0.5659782814660992,"score_spread":0.20133537284186193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386751706","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919655,0.00006269984,0.00091714185,0.0030017695,0.0026655528,0.00047524305,0.00085495616,0.000019520217,0.000037651782],"genre_scores_gemma":[0.99438834,0.00019029138,0.0018585101,0.00013566036,0.0002780283,0.0000027602362,0.002513073,0.000009347224,0.0006239601],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970111,0.00020370945,0.0009192158,0.00044040658,0.0010347957,0.00039072605],"domain_scores_gemma":[0.9971199,0.00048507666,0.00075756566,0.00074103114,0.0006680249,0.00022841064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036202164,0.00010051958,0.00018797799,0.000660843,0.001061687,0.000158702,0.0023093228,0.00005197232,0.000025938218],"category_scores_gemma":[0.0022273494,0.00007877519,0.000021388629,0.002014907,0.00012874488,0.0026381076,0.00063806033,0.0002375204,0.0000010040242],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010449933,0.000017411972,0.9861924,0.000007868809,0.00006330758,0.0000036269826,0.0003881046,0.0006368178,0.000051881718,0.0048092566,0.0042777243,0.0034470854],"study_design_scores_gemma":[0.00039669924,0.000035005567,0.8167089,0.00012399512,0.0000485623,0.000005073657,0.0031956092,0.16977751,0.0000028184124,0.00090691546,0.008717758,0.00008114136],"about_ca_topic_score_codex":0.66011536,"about_ca_topic_score_gemma":0.9602146,"teacher_disagreement_score":0.30009925,"about_ca_system_score_codex":0.00042604154,"about_ca_system_score_gemma":0.006139834,"threshold_uncertainty_score":0.99949443},"labels":[],"label_agreement":null},{"id":"W4386751842","doi":"10.23889/ijpds.v8i2.2356","title":"Maternal disability and newborn discharge to child protection in Ontario, Canada","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homicide, Infanticide, and Child Abuse","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Multiple Sclerosis Society of Canada; University of Toronto; Women's College Hospital; The Scarborough Hospital; Hospital for Sick Children; Institute for Clinical Evaluative Sciences; Centre for Addiction and Mental Health","funders":"","keywords":"Medicine; Breastfeeding; Cohort; Poisson regression; Population; Receipt; Mental health; Cohort study; Intervention (counseling); Environmental health; Pediatrics; Psychiatry","score_opus":0.04647607228237714,"score_gpt":0.3502907543523253,"score_spread":0.30381468206994816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386751842","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881528,0.00000269764,0.00048427848,0.008319668,0.0021904155,0.00032811123,0.000116428266,0.00001990732,0.00038569633],"genre_scores_gemma":[0.9987048,0.0000119805345,0.0004248609,0.00020640377,0.00033470406,0.000009116551,0.0000665379,0.0000048381135,0.0002367464],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99813616,0.00003983015,0.00031245782,0.00031483968,0.00090474135,0.00029195187],"domain_scores_gemma":[0.9993051,0.000045522793,0.00011452625,0.00018374342,0.00016104872,0.00019004963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018278743,0.000074938,0.000090115675,0.00017577231,0.0007624646,0.0004224887,0.0010090829,0.000026592805,0.00007859931],"category_scores_gemma":[0.0007776055,0.00006982578,0.000017605062,0.00039475018,0.00015495913,0.0016100252,0.00019799535,0.00016142896,0.0000051049087],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036849076,0.00001625092,0.98572487,0.0000016782486,0.0000053265153,0.000003701587,0.0011508756,0.00023694999,0.00006441123,0.0040855035,0.00053222827,0.008141371],"study_design_scores_gemma":[0.00018831623,0.00001013823,0.95535254,0.000039859944,0.000002286772,0.000010315268,0.0003864708,0.0016760714,0.0000216709,0.00096939487,0.041257445,0.00008548613],"about_ca_topic_score_codex":0.9737032,"about_ca_topic_score_gemma":0.9981581,"teacher_disagreement_score":0.040725216,"about_ca_system_score_codex":0.00095811207,"about_ca_system_score_gemma":0.0006595424,"threshold_uncertainty_score":0.5864338},"labels":[],"label_agreement":null},{"id":"W4386833842","doi":"10.23889/ijpds.v8i3.2286","title":"Decoy Effects in a Massive Real-World Shopping Dataset","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Wine Industry and Tourism","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Premise; Quality (philosophy); Wine; Database transaction; Preference; Set (abstract data type); Choice set; Computer science; Advertising; Marketing; Economics; Business; Microeconomics; Econometrics","score_opus":0.07837637886564754,"score_gpt":0.38071343194525076,"score_spread":0.30233705307960324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386833842","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94324744,0.000011283381,0.003638451,0.031385586,0.016027456,0.0007979766,0.0013459409,0.00020508196,0.0033408087],"genre_scores_gemma":[0.9843042,0.000005602666,0.000747096,0.0008568069,0.0068891603,0.000011928046,0.0068844343,0.000013007253,0.00028775114],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9985118,0.0000071757463,0.00031319505,0.00030390566,0.0006105925,0.0002533105],"domain_scores_gemma":[0.999158,0.00010763966,0.00025117537,0.000268538,0.00019220283,0.000022401708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014220709,0.000089699985,0.00009311104,0.0012078786,0.0002880287,0.00081920496,0.00159,0.00002697816,0.00005495897],"category_scores_gemma":[0.0010663487,0.00008345773,0.000024454472,0.0012010167,0.00005077533,0.0069444505,0.0006339834,0.00016093829,0.00010872779],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000096765034,0.000090938345,0.4130262,0.000053315634,0.000038195187,0.00031989362,0.000030898125,0.008199038,0.00070516835,0.037727244,0.51814014,0.021572184],"study_design_scores_gemma":[0.0007622701,0.000005423081,0.59785503,0.00016716635,0.000013626538,0.00001374906,0.00004917286,0.20785889,0.000017310977,0.010742203,0.18231957,0.00019558085],"about_ca_topic_score_codex":0.0008578823,"about_ca_topic_score_gemma":0.0003389059,"teacher_disagreement_score":0.33582056,"about_ca_system_score_codex":0.000089050714,"about_ca_system_score_gemma":0.000055374996,"threshold_uncertainty_score":0.7899612},"labels":[],"label_agreement":null},{"id":"W4386833854","doi":"10.23889/ijpds.v8i3.2285","title":"SynthEco - A multi-layered digital ecosystem for analysing complex human behaviour in context","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Dawson College; McGill University; Université Laval","funders":"","keywords":"Geospatial analysis; Computer science; Context (archaeology); Data science; Population; Data mining; Geography; Granularity; Environmental resource management; Cartography; Environmental science","score_opus":0.21414637967186942,"score_gpt":0.48043497983576416,"score_spread":0.2662886001638948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386833854","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9394932,0.000010822911,0.054318886,0.0024617712,0.0010752551,0.0006261788,0.001814192,0.000080309816,0.0001194207],"genre_scores_gemma":[0.99703926,0.0000047287876,0.00071175385,0.00005484662,0.00032051417,0.000024416102,0.001522885,0.000008535381,0.00031304185],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976994,0.000070540256,0.00060510566,0.00041433008,0.0008834956,0.0003271283],"domain_scores_gemma":[0.998218,0.00029620135,0.00033069545,0.00028210302,0.0007350129,0.00013800149],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0040511163,0.000097018004,0.00017515346,0.00083214947,0.0014798772,0.0012026973,0.001793495,0.000046703637,0.00005743817],"category_scores_gemma":[0.0021765286,0.0000988213,0.00011396292,0.0008752779,0.00017986921,0.0025207412,0.00013571321,0.00009868393,0.000015922467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019244461,0.00091128296,0.66224694,0.00005408446,0.0003158716,0.000029166711,0.010382329,0.033887375,0.0026802218,0.14001498,0.0028432219,0.14644212],"study_design_scores_gemma":[0.0014653844,0.000046345238,0.115687,0.00013856396,0.00005174959,0.000006165391,0.0136312805,0.84880817,0.000029475685,0.0036222714,0.016142396,0.00037121994],"about_ca_topic_score_codex":0.0029005553,"about_ca_topic_score_gemma":0.06446532,"teacher_disagreement_score":0.8149208,"about_ca_system_score_codex":0.00046537747,"about_ca_system_score_gemma":0.00031479335,"threshold_uncertainty_score":0.9998341},"labels":[],"label_agreement":null},{"id":"W4386888372","doi":"10.23889/ijpds.v8i4.2142","title":"Essential requirements for the governance and management of data trusts, data repositories, and other data collaborations","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Research Data Management Practices","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; University of Toronto; Université de Sherbrooke; Health Sciences Centre; Centre for Addiction and Mental Health; North York General Hospital; St. Michael's Hospital; Sunnybrook Health Science Centre; Institute for Clinical Evaluative Sciences; Public Health Agency of Canada; St. Paul's Hospital; Diabetes Canada; University of New Brunswick; Indoc Research; Vector Institute","funders":"Canadian Institutes of Health Research","keywords":"Data governance; Corporate governance; Stakeholder; Data management; Data sharing; Computer science; Business; Engineering; Political science; Public relations; Operations management; Data quality; Finance; Database","score_opus":0.3443295514248307,"score_gpt":0.4959817831033048,"score_spread":0.15165223167847414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386888372","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017825242,0.000489359,0.9476822,0.017387433,0.0037401426,0.0012386381,0.02750972,0.000047748363,0.00012220613],"genre_scores_gemma":[0.26401997,0.023563107,0.6703753,0.00065192214,0.0020103757,0.00008692658,0.03668428,0.00005765575,0.002550488],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966263,0.000050857314,0.0004856134,0.0010565558,0.0015347046,0.0002459265],"domain_scores_gemma":[0.99280125,0.00045276806,0.0005878474,0.0056949705,0.00038215338,0.000081037324],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.007250003,0.000102359765,0.000103775405,0.00016308152,0.00072379806,0.0043483474,0.027279437,0.00001897629,0.0000030111028],"category_scores_gemma":[0.0019754074,0.00008044591,0.000007744201,0.00081488944,0.00022756006,0.06922189,0.026711976,0.00008676236,0.0000011609817],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018081065,0.0001434133,0.010161705,0.00015950507,0.0006471059,0.000026262345,0.00013339349,0.0002665177,0.0004897859,0.7090134,0.14775717,0.1310209],"study_design_scores_gemma":[0.00048691517,0.000022734237,0.01897346,0.00006319433,0.000046581437,0.000021889822,0.00011109955,0.6084289,0.000015047801,0.0009621468,0.37077042,0.000097614364],"about_ca_topic_score_codex":0.00025492418,"about_ca_topic_score_gemma":0.00022640526,"teacher_disagreement_score":0.70805126,"about_ca_system_score_codex":0.000043027234,"about_ca_system_score_gemma":0.00016852393,"threshold_uncertainty_score":0.9966852},"labels":[],"label_agreement":null},{"id":"W4387133168","doi":"10.23889/ijpds.v8i5.2177","title":"Understanding data provenance when using electronic medical records for research: Lessons learned from the Deliver Primary Healthcare Information (DELPHI) database","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Western University","funders":"Lawson Health Research Institute","keywords":"Data quality; Database; Health care; Computer science; Identifier; Record linkage; Delphi; Data science; Medicine; Metric (unit); Engineering; Operations management","score_opus":0.8682030873622053,"score_gpt":0.6389304617001106,"score_spread":0.22927262566209472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387133168","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06503023,0.00055924756,0.6004111,0.2880978,0.017341074,0.006395262,0.021726679,0.00025469763,0.00018391303],"genre_scores_gemma":[0.91467273,0.0034912012,0.012635489,0.006668761,0.007338404,0.000345292,0.05437167,0.00009387,0.00038256656],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9925289,0.0008073109,0.0013719329,0.0006860877,0.0032094982,0.0013962595],"domain_scores_gemma":[0.9917496,0.0038402406,0.0009200179,0.0014997631,0.0016458563,0.0003445475],"candidate_categories":["metaresearch","sts","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.036408138,0.00016033414,0.0002409747,0.00055629114,0.004487063,0.00030557215,0.006065815,0.0001663488,0.00006928933],"category_scores_gemma":[0.01589587,0.00012416925,0.000042005446,0.00093387894,0.000212406,0.0069084163,0.0020862932,0.0015659262,0.000047389814],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.0019023648,0.00013690242,0.040344372,0.00078101445,0.0002809787,0.000015056072,0.0075929994,0.00065198855,0.0006894214,0.22010316,0.5411831,0.18631859],"study_design_scores_gemma":[0.00180209,0.00011602599,0.0056231134,0.0013828272,0.000023209668,0.0000331577,0.004270471,0.6914776,0.000003162451,0.0653888,0.22963196,0.00024758285],"about_ca_topic_score_codex":0.006970104,"about_ca_topic_score_gemma":0.0072851027,"teacher_disagreement_score":0.8496425,"about_ca_system_score_codex":0.0041596713,"about_ca_system_score_gemma":0.009958905,"threshold_uncertainty_score":0.9996632},"labels":[],"label_agreement":null},{"id":"W4387668118","doi":"10.23889/ijpds.v8i1.2123","title":"Orthopedic and ophthalmology surgical service projection modelling in Manitoba: Research approach for a data linkage study","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Orthopedic surgery; Workload; Medicine; Medical emergency; Health care; Population; Emergency medicine; Surgery; Computer science; Environmental health","score_opus":0.7446905875689289,"score_gpt":0.6405270228312377,"score_spread":0.10416356473769117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387668118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90081817,0.000027552192,0.0915355,0.0026577432,0.0016955024,0.002697427,0.0004314559,0.00003913992,0.00009752033],"genre_scores_gemma":[0.951411,0.000105311454,0.042605605,0.000066872824,0.00085613,0.00022753276,0.00453465,0.000018943765,0.00017395258],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99680376,0.00046082697,0.00076676457,0.0006825899,0.0008413372,0.00044474337],"domain_scores_gemma":[0.9966349,0.0006917412,0.00019992453,0.00055338634,0.0017979986,0.00012205727],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.018768214,0.000093130846,0.00015518037,0.00097209425,0.0020293924,0.00020860646,0.0014352883,0.000105851585,0.000009341917],"category_scores_gemma":[0.0017605596,0.00008282969,0.000012006656,0.0013403632,0.000060005168,0.0020616085,0.0009424536,0.00057955383,0.0000061033384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007847548,0.00070032716,0.7466849,0.00027823538,0.00005798825,0.00006991921,0.005706213,0.2211853,0.00004910187,0.005062738,0.0016604974,0.01776002],"study_design_scores_gemma":[0.0010321325,0.00008551626,0.02111566,0.000060923117,0.0000054370685,0.00006394664,0.0044093076,0.9716041,1.5062278e-7,0.00041194202,0.0011318643,0.000079001635],"about_ca_topic_score_codex":0.0030755762,"about_ca_topic_score_gemma":0.001358739,"teacher_disagreement_score":0.75041884,"about_ca_system_score_codex":0.00024063386,"about_ca_system_score_gemma":0.00073678204,"threshold_uncertainty_score":0.99926984},"labels":[],"label_agreement":null},{"id":"W4387957258","doi":"10.23889/ijpds.v8i4.2160","title":"Health Data Governance for Research Use in Alberta","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian VIGOUR Centre; Alberta Health Services; University of Alberta; University of Calgary","funders":"","keywords":"Custodians; Data governance; General partnership; Corporate governance; Analytics; Big data; Research ethics; Business; Data sharing; Data science; Medicine; Knowledge management; Data quality; Service (business); Computer science; Data mining; Geography; Alternative medicine; Marketing; Finance","score_opus":0.9164866338083132,"score_gpt":0.7551595823879634,"score_spread":0.16132705142034975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387957258","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32448602,0.00022384399,0.014902843,0.6349644,0.010819325,0.0042952015,0.009659164,0.000098521225,0.0005506744],"genre_scores_gemma":[0.9618377,0.0015813905,0.022708688,0.0011991228,0.0011387058,0.000032517477,0.004950653,0.000029789611,0.0065214513],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99432206,0.00008253928,0.0007379661,0.0007530349,0.003530077,0.00057434815],"domain_scores_gemma":[0.98327905,0.012111855,0.00026805297,0.0016730638,0.0023394309,0.00032853763],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03653824,0.00007592488,0.00018112315,0.00057885394,0.00043581336,0.00045679932,0.004634443,0.00008009195,0.000022607544],"category_scores_gemma":[0.17241253,0.00006687429,0.000034981855,0.0011713759,0.0003282395,0.0029473698,0.002114649,0.0009960482,0.000034127064],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015942956,0.000464074,0.40389636,0.00021988708,0.0000788299,0.00005999995,0.00032198886,0.00054456363,0.00055728643,0.30828428,0.19200921,0.09196921],"study_design_scores_gemma":[0.0020266678,0.00027543184,0.5806135,0.0007416171,0.0000048786374,0.00008113262,0.00008750316,0.24541628,0.000023553104,0.054880306,0.11571909,0.0001300435],"about_ca_topic_score_codex":0.004941518,"about_ca_topic_score_gemma":0.01786373,"teacher_disagreement_score":0.6373517,"about_ca_system_score_codex":0.00053803285,"about_ca_system_score_gemma":0.0022495321,"threshold_uncertainty_score":0.99683803},"labels":[],"label_agreement":null},{"id":"W4389036121","doi":"10.23889/ijpds.v8i1.2176","title":"Generating synthetic data from administrative health records for drug safety and effectiveness studies","year":2023,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal; Manitoba Health; McGill University; University of Manitoba","funders":"Canadian Institutes of Health Research","keywords":"Real world data; Population; Medical prescription; Computer science; Medicine; Data science; Pharmacology; Environmental health","score_opus":0.5555152502297888,"score_gpt":0.5974494260819023,"score_spread":0.041934175852113564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389036121","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15980192,0.00023234302,0.82378197,0.0031264692,0.002617036,0.001150037,0.009062573,0.00020857251,0.000019085159],"genre_scores_gemma":[0.6228616,0.0006085171,0.37295163,0.00014164204,0.0005569172,0.000052809977,0.0027212673,0.000027720671,0.00007788577],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980444,0.00010036679,0.0005399996,0.00055676984,0.00052597985,0.00023249057],"domain_scores_gemma":[0.99503297,0.003146146,0.00050091057,0.0005968378,0.000630289,0.00009284207],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005590062,0.00013005844,0.00024181826,0.0001984724,0.0006558919,0.00026719325,0.0016296565,0.000024170507,0.0000062607633],"category_scores_gemma":[0.012366887,0.00011155628,0.000023572758,0.00022123793,0.00016735893,0.002600687,0.0008747869,0.00011847503,0.0000013648024],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021022111,0.0004566848,0.022514367,0.00077881536,0.0012589147,0.000040202554,0.005841257,0.0020476647,0.011794378,0.3871595,0.07305709,0.49294892],"study_design_scores_gemma":[0.0008291127,0.00018619382,0.00859043,0.0008108617,0.00004217279,0.000053201027,0.0012845317,0.33309636,0.00088974583,0.65009564,0.0037783606,0.0003433649],"about_ca_topic_score_codex":0.00007823215,"about_ca_topic_score_gemma":0.00030117348,"teacher_disagreement_score":0.49260557,"about_ca_system_score_codex":0.0002328311,"about_ca_system_score_gemma":0.00022074298,"threshold_uncertainty_score":0.99595237},"labels":[],"label_agreement":null},{"id":"W4389615820","doi":"10.23889/ijpds.v8i1.2153","title":"De-identification of Free Text Data containing Personal Health Information: A Scoping Review of Reviews","year":2023,"lang":"en","type":"review","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; George & Fay Yee Centre for Healthcare Innovation; Manitoba Health","funders":"Canadian Institutes of Health Research","keywords":"Health Insurance Portability and Accountability Act; Identification (biology); Computer science; Protected health information; Information retrieval; MEDLINE; Personally identifiable information; Digital library; Data science; World Wide Web; Medicine; Confidentiality; Public health; Nursing; Health education","score_opus":0.7026193400916434,"score_gpt":0.6308973187983484,"score_spread":0.07172202129329497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389615820","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.649742e-7,0.9250688,0.05741154,0.0011832913,0.0022805717,0.0017910029,0.012197019,0.000014259278,0.00005314205],"genre_scores_gemma":[0.000005274331,0.98431915,0.004617844,0.0004737379,0.00023154015,0.0000310523,0.010214936,0.00001095169,0.000095484735],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9875827,0.0005568905,0.0066171163,0.0007229413,0.0042162123,0.00030417836],"domain_scores_gemma":[0.98135316,0.0013995569,0.011864572,0.0033798777,0.001826005,0.00017680512],"candidate_categories":["metaresearch","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.07437966,0.00022600382,0.0014526079,0.0013589668,0.00033256708,0.000942666,0.018078167,0.00006471051,0.00011772373],"category_scores_gemma":[0.065756746,0.00017383139,0.00025891868,0.0017979313,0.00022182544,0.009249598,0.0042995503,0.00024999474,0.00006816018],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059103154,0.000019442978,0.000008429448,0.027133722,0.00004269615,4.79978e-7,0.00009950463,0.0000041315157,1.17543735e-7,0.0024432684,0.03728007,0.93296224],"study_design_scores_gemma":[0.00013054423,0.000028470955,0.000038085498,0.22073941,0.000094870455,0.00003741265,0.00009098175,0.0020462496,1.1335901e-7,0.000857024,0.7758035,0.0001333251],"about_ca_topic_score_codex":0.00014992968,"about_ca_topic_score_gemma":0.00007457093,"teacher_disagreement_score":0.9328289,"about_ca_system_score_codex":0.00029084267,"about_ca_system_score_gemma":0.0025606304,"threshold_uncertainty_score":0.9872345},"labels":[],"label_agreement":null},{"id":"W4392911424","doi":"10.23889/ijpds.v9i1.2364","title":"Defining a low-risk birth cohort: a cohort study comparing two perinatal data sets in Ontario, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal and Perinatal Health Interventions","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; McMaster University","funders":"","keywords":"Medicine; Cohort; Demography; Population; Cohort study; Health care; Family medicine; Pediatrics; Environmental health; Internal medicine","score_opus":0.07696986520614181,"score_gpt":0.42324223540109845,"score_spread":0.34627237019495666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392911424","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99183106,0.00012992446,0.00063831726,0.00036574114,0.004151035,0.0005628726,0.002082426,0.000026045436,0.00021258855],"genre_scores_gemma":[0.9962587,0.000016377233,0.001045334,0.00008608611,0.00016577114,0.000019151797,0.0015937033,0.000013725029,0.0008011785],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969579,0.000040381972,0.0007340469,0.0006505968,0.0013083428,0.00030871175],"domain_scores_gemma":[0.99858737,0.00009225476,0.00019351393,0.0006430598,0.0002677269,0.00021608305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002582332,0.00014363989,0.00023627505,0.0004178584,0.00031248256,0.00046544452,0.0016531746,0.000022046854,0.0004253816],"category_scores_gemma":[0.00045131086,0.00012522413,0.00003759276,0.0003045672,0.000058513615,0.0018246508,0.00083827344,0.00051915005,0.000010389741],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010876068,0.0000962597,0.9937611,0.00006030359,0.00007597995,0.00028576708,0.000114530536,0.00026481823,0.0000051020766,0.00044974504,0.0005577964,0.004219809],"study_design_scores_gemma":[0.0007025579,0.00007635869,0.82539815,0.00042156116,0.00002815243,0.00072000426,0.00008272693,0.15798038,0.0000027641127,0.0000959155,0.014386865,0.000104589766],"about_ca_topic_score_codex":0.94850856,"about_ca_topic_score_gemma":0.9826531,"teacher_disagreement_score":0.168363,"about_ca_system_score_codex":0.0012875083,"about_ca_system_score_gemma":0.0020147215,"threshold_uncertainty_score":0.51064914},"labels":[],"label_agreement":null},{"id":"W4393039023","doi":"10.23889/ijpds.v9i1.2368","title":"The centre for health informatics: a novel approach to accelerating the field of health data science","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; University of Calgary","funders":"","keywords":"Health informatics; Multidisciplinary approach; Digital health; Public health informatics; Population health; Informatics; Data science; Health Administration Informatics; Knowledge management; Clinical decision support system; Population; Raw data; Public health; Medicine; Health care; Health policy; Business; Computer science; HRHIS; Engineering; Environmental health; Decision support system; Political science; Nursing; Data mining","score_opus":0.3162393287102499,"score_gpt":0.5874666931277034,"score_spread":0.2712273644174535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393039023","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005633323,0.0007884283,0.72917604,0.24009949,0.015869288,0.0052204235,0.0024724675,0.00007046783,0.0006700422],"genre_scores_gemma":[0.8566102,0.00046605102,0.11867663,0.018931512,0.003102104,0.00020731366,0.0011272853,0.000048120597,0.00083082577],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9951027,0.00015008259,0.001981818,0.0004173681,0.0014913231,0.00085668836],"domain_scores_gemma":[0.9941017,0.0023685026,0.0011538803,0.0011345549,0.0009958398,0.00024553385],"candidate_categories":["metaresearch","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.035293926,0.000117256444,0.00020750602,0.00033010705,0.0051150066,0.00053826335,0.0065995106,0.000037380043,0.000005637447],"category_scores_gemma":[0.0082851285,0.00006819736,0.000035864934,0.0009174683,0.00017084146,0.003099649,0.0012489252,0.00050764566,0.0000060883813],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014765175,0.00012498275,0.0042213215,0.0011829517,0.00008023308,1.7141431e-7,0.01587508,0.0011273375,0.00027891333,0.26906398,0.27346307,0.43443432],"study_design_scores_gemma":[0.00030906964,0.000114098395,0.0023136628,0.0006751815,0.0000043685045,0.000021119144,0.0037439715,0.557096,0.0000047074664,0.00061501615,0.4350122,0.000090601745],"about_ca_topic_score_codex":0.0011630493,"about_ca_topic_score_gemma":0.00074493984,"teacher_disagreement_score":0.8509768,"about_ca_system_score_codex":0.0009303783,"about_ca_system_score_gemma":0.009453738,"threshold_uncertainty_score":0.99877524},"labels":[],"label_agreement":null},{"id":"W4394892935","doi":"10.23889/ijpds.v9i1.2375","title":"Health data social licence: An inclusive process to learn more about the perspectives of experienced public and patient advisors","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Health and Social Services Centre University Institute of Geriatrics of Sherbrooke; Canadian Respiratory Research Network; Université de Sherbrooke","funders":"Public Health Agency; Public Health Agency of Canada; Université de Sherbrooke","keywords":"Public health; Health care; Agency (philosophy); Public relations; Health informatics; Psychology; Medical education; Medicine; Political science; Nursing; Sociology; Social science","score_opus":0.44400932820266675,"score_gpt":0.6610736761305986,"score_spread":0.2170643479279319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394892935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86387485,0.0004336915,0.003060708,0.13079911,0.0007545189,0.0004958797,0.0004947345,0.000019153653,0.00006737293],"genre_scores_gemma":[0.99618,0.00020178502,0.002157516,0.00083428144,0.00037418585,0.000009842418,0.00019560054,0.000008537877,0.000038254657],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.9964153,0.000057445217,0.000476903,0.0005496438,0.0022796486,0.00022102694],"domain_scores_gemma":[0.99661875,0.0006358341,0.0001965023,0.0005344709,0.0017646857,0.0002497572],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0047869408,0.00007693955,0.00013747923,0.00029422226,0.0006203609,0.0004657094,0.0024096752,0.000046304594,0.000031442276],"category_scores_gemma":[0.015482532,0.000051517934,0.000024043271,0.0005372239,0.00068070804,0.0023967896,0.0013984133,0.000565655,0.0000013633505],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00074669986,0.00070382876,0.025736982,0.00026624545,0.00018654327,0.000028416833,0.3127756,0.00020643615,0.0014879312,0.1406895,0.003947464,0.5132243],"study_design_scores_gemma":[0.001605681,0.0024960851,0.30294615,0.0019023728,0.000052437346,0.0005791244,0.39273524,0.24594189,0.00023919533,0.032162443,0.018827219,0.0005121443],"about_ca_topic_score_codex":0.00015812226,"about_ca_topic_score_gemma":0.00018344575,"teacher_disagreement_score":0.5127122,"about_ca_system_score_codex":0.0002070647,"about_ca_system_score_gemma":0.0018654757,"threshold_uncertainty_score":0.9928105},"labels":[],"label_agreement":null},{"id":"W4396511904","doi":"10.23889/ijpds.v9i1.2358","title":"Trend control charts for multiple sclerosis case definitions","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; University of Manitoba","funders":"","keywords":"Multiple sclerosis; Control (management); Computer science; Data science; Natural language processing; Psychology; Artificial intelligence; Psychiatry","score_opus":0.20951296168717207,"score_gpt":0.4038379860269997,"score_spread":0.19432502433982765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396511904","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48145932,0.0013622367,0.30695364,0.014946896,0.020469679,0.0028737143,0.17080459,0.0005290077,0.00060089404],"genre_scores_gemma":[0.98498905,0.000053303513,0.009006267,0.00038886123,0.0008130123,0.000044796023,0.0046037827,0.000016999875,0.00008392504],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983463,0.000014879602,0.00039254752,0.00041227273,0.00060279795,0.00023117171],"domain_scores_gemma":[0.9986135,0.0003087364,0.00011845045,0.0003643297,0.00037613144,0.00021887907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009615441,0.00010673412,0.00014334264,0.0004069756,0.00037333972,0.0005025579,0.0005716625,0.000029073994,0.000075953685],"category_scores_gemma":[0.0016680898,0.000092867944,0.000108811975,0.00025780493,0.00011744943,0.0018218145,0.00010071966,0.00010803755,0.000016454722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003167189,0.0013019532,0.091863096,0.00042992004,0.0015247684,0.003463995,0.0006252294,0.0020710095,0.024271466,0.08274215,0.2070931,0.5814461],"study_design_scores_gemma":[0.006167144,0.00024750002,0.08584666,0.0007166113,0.00030979933,0.0115459785,0.00012782853,0.68934,0.00020780442,0.0038607027,0.20121326,0.000416715],"about_ca_topic_score_codex":0.000053727952,"about_ca_topic_score_gemma":0.0001332723,"teacher_disagreement_score":0.687269,"about_ca_system_score_codex":0.00017554652,"about_ca_system_score_gemma":0.00021478854,"threshold_uncertainty_score":0.48461774},"labels":[],"label_agreement":null},{"id":"W4398141288","doi":"10.23889/ijpds.v9i1.2378","title":"Semantically Interoperable Census Data: Unlocking the Semantics of Census Data Using Ontologies and Linked Data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Tata Consultancy Services","keywords":"Census; Computer science; Ontology; Data science; Population; Data mining; American Community Survey; Interoperability; Geography; Information retrieval; World Wide Web","score_opus":0.68581780609668,"score_gpt":0.5772460683615351,"score_spread":0.10857173773514484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398141288","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1397323,0.001543058,0.70231,0.041516487,0.02148393,0.0010313794,0.09192959,0.00011821622,0.00033502743],"genre_scores_gemma":[0.9446987,0.00037848353,0.044696,0.00032690237,0.00052912114,8.0089313e-7,0.009200721,0.000014626903,0.00015467065],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9945123,0.00016573095,0.0011535437,0.0012747971,0.0025988885,0.00029473737],"domain_scores_gemma":[0.99172205,0.0014640013,0.00050345884,0.0055886335,0.0006184864,0.00010339878],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.019227069,0.00015258131,0.00023842577,0.0003744753,0.0005647307,0.0038436665,0.024864037,0.00004382437,0.000038437054],"category_scores_gemma":[0.016471587,0.00009560419,0.00002523013,0.0007080874,0.0005843548,0.0115946205,0.026887704,0.00026721685,0.000008503472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031153933,0.00031455402,0.01938727,0.00015512871,0.0006500749,0.00016952514,0.00083176576,0.005452796,0.0022810404,0.09968516,0.2818421,0.58891904],"study_design_scores_gemma":[0.00016658942,0.000017644492,0.004377576,0.00015257963,0.000066539906,0.00014795236,0.00058980857,0.7979875,0.000010441829,0.006960326,0.18940373,0.00011927742],"about_ca_topic_score_codex":0.00064141833,"about_ca_topic_score_gemma":0.0006273429,"teacher_disagreement_score":0.8049664,"about_ca_system_score_codex":0.00006463717,"about_ca_system_score_gemma":0.00020461692,"threshold_uncertainty_score":0.9971904},"labels":[],"label_agreement":null},{"id":"W4398782656","doi":"10.23889/ijpds.v9i3.2460","title":"The Royal Marsden BRIDgE TRE Transparency Project","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Structural Engineering and Vibration Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Cancer Research","funders":"","keywords":"Bridge (graph theory); Transparency (behavior); Archaeology; Engineering; History; Political science; Law; Medicine; Anatomy","score_opus":0.05026116801889933,"score_gpt":0.36134798893416553,"score_spread":0.3110868209152662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398782656","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056958925,0.0016416595,0.917358,0.0021767286,0.019056266,0.0002903633,0.0007697094,0.0005387701,0.0012096195],"genre_scores_gemma":[0.9978187,0.00011011334,0.001111458,0.000014435444,0.00045371367,0.0000052012115,0.00017970991,0.000010970282,0.0002956647],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896735,0.000006516053,0.00024845143,0.00016413753,0.00046389783,0.00014962009],"domain_scores_gemma":[0.9995595,0.000066520544,0.000024467694,0.00019222416,0.0001104529,0.000046793437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045932428,0.000078650526,0.000055452078,0.00020344046,0.00025408214,0.00095002464,0.0010668545,0.000019420855,0.00002668275],"category_scores_gemma":[0.000102750964,0.000054022014,0.000051699735,0.000302443,0.00005213355,0.0010064436,0.000037604947,0.00012285708,0.000007739832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018797062,0.0000062718677,0.00059210404,0.000028384999,0.0002206125,0.000013384021,0.0002699369,0.44880012,0.00087787147,0.016778052,0.02882556,0.5035689],"study_design_scores_gemma":[0.00006387571,0.0000061081128,0.007851377,0.000024922188,0.000013709393,0.000033792025,0.00001925864,0.93370175,0.0000676483,0.00046248423,0.057680618,0.000074477924],"about_ca_topic_score_codex":0.000052495903,"about_ca_topic_score_gemma":0.000040037132,"teacher_disagreement_score":0.9408598,"about_ca_system_score_codex":0.00011065887,"about_ca_system_score_gemma":0.000059122434,"threshold_uncertainty_score":0.91611093},"labels":[],"label_agreement":null},{"id":"W4399856871","doi":"10.23889/ijpds.v9i1.2385","title":"Can administrative data be used to research health visiting in England? A completeness assessment of the Community Services Dataset","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Infant Development and Preterm Care","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Public Health Research Programme; Department of Health and Social Care; National Institute for Health and Care Research","keywords":"Representativeness heuristic; Quarter (Canadian coin); Visitor pattern; Community health; Medicine; Family medicine; Public health; Geography; Psychology; Computer science; Nursing","score_opus":0.4868008288389045,"score_gpt":0.593156148151955,"score_spread":0.10635531931305053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399856871","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9168992,0.000026161348,0.00034025058,0.024274353,0.0010726405,0.0005245145,0.056772977,0.000007897814,0.00008197977],"genre_scores_gemma":[0.9551167,0.000007717845,0.004044306,0.00051003206,0.00012162096,0.000004522179,0.040184326,0.000004684674,0.000006086535],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976465,0.00021963668,0.0004166352,0.00024202358,0.0012883253,0.00018684991],"domain_scores_gemma":[0.99825937,0.0003630081,0.00012929317,0.0007377166,0.0004158839,0.00009475403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008432709,0.000064569904,0.0001244086,0.0003555617,0.00044407588,0.0003032215,0.002699227,0.000017564806,0.00002139178],"category_scores_gemma":[0.00047787782,0.00004598648,0.00001431034,0.0005555442,0.000091824,0.0009520288,0.0014113493,0.00044047824,2.5803286e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004098128,0.00017720685,0.9116124,0.0007761278,0.00020490326,0.00007437908,0.029572433,0.00026161445,0.0045731235,0.00935688,0.0110740755,0.031907063],"study_design_scores_gemma":[0.0010127429,0.00022206204,0.8157865,0.0023908985,0.000015665437,0.00024144983,0.00281587,0.092133805,0.00021415311,0.0008590106,0.08414506,0.00016278446],"about_ca_topic_score_codex":0.0029241971,"about_ca_topic_score_gemma":0.012716783,"teacher_disagreement_score":0.09582588,"about_ca_system_score_codex":0.0002674886,"about_ca_system_score_gemma":0.0012983172,"threshold_uncertainty_score":0.7096263},"labels":[],"label_agreement":null},{"id":"W4400320834","doi":"10.23889/ijpds.v9i2.2396","title":"Maternal disability and newborn discharge to social services: a population-based study","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal Mental Health During Pregnancy and Postpartum","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Public Health Ontario; The Scarborough Hospital; Hospital for Sick Children; Women's College Hospital; University of Toronto; SickKids Foundation; Centre for Addiction and Mental Health","funders":"Economic and Social Research Council; Canadian Institutes of Health Research; Mitacs; Canada Research Chairs; UK Research and Innovation","keywords":"Population; Psychology; Medicine; Developmental psychology; Environmental health","score_opus":0.05473354927275509,"score_gpt":0.4299101125204729,"score_spread":0.3751765632477178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400320834","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.990949,0.000044778953,0.0011692223,0.0039644437,0.002581094,0.0006129678,0.00060935144,0.000047064685,0.00002212799],"genre_scores_gemma":[0.9963366,0.0000035345138,0.001976156,0.00046480258,0.0007352517,0.00002069305,0.00034495685,0.000012944849,0.000105083986],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980154,0.000029804987,0.00043474874,0.00043674425,0.0008577603,0.00022554702],"domain_scores_gemma":[0.99922556,0.000057262034,0.00009418236,0.00022617256,0.00016228222,0.00023452965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009616389,0.00011933213,0.0001450177,0.00020503197,0.00041023883,0.00056399714,0.0005489627,0.000028625225,0.000054961725],"category_scores_gemma":[0.00006482153,0.00009611015,0.00003821117,0.00020240055,0.000046099718,0.0011699212,0.00020548838,0.00014413214,0.00001212892],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032932364,0.00014042546,0.9885876,0.00037736088,0.00002419417,0.00001583902,0.0002583443,0.00002631569,0.0000723251,0.0006523665,0.000023262339,0.009492616],"study_design_scores_gemma":[0.00052767154,0.00015779163,0.98321486,0.00096100115,0.000031282678,0.00008644864,0.00006945905,0.013044041,0.00003246707,0.00038712012,0.0013957885,0.0000920988],"about_ca_topic_score_codex":0.0009443786,"about_ca_topic_score_gemma":0.00025754934,"teacher_disagreement_score":0.013017725,"about_ca_system_score_codex":0.00027214663,"about_ca_system_score_gemma":0.00009582428,"threshold_uncertainty_score":0.5438637},"labels":[],"label_agreement":null},{"id":"W4400654080","doi":"10.23889/ijpds.v9i2.2401","title":"Global trends in prevalence of maternal overweight and obesity: A systematic review and meta-analysis of routinely collected data retrospective cohorts","year":2024,"lang":"en","type":"review","venue":"International Journal for Population Data Science","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Queen's University; Queen's University Belfast","keywords":"Overweight; Obesity; Meta-analysis; Medicine; Environmental health; Internal medicine","score_opus":0.16457764357802254,"score_gpt":0.4826370919512163,"score_spread":0.3180594483731938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400654080","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014438489,0.981742,0.00016147754,0.00017896836,0.00010800698,0.0012108473,0.016410764,0.000004941499,0.000038585764],"genre_scores_gemma":[0.0035855947,0.9919386,0.0009510008,0.000038015358,0.000019858728,0.00003884463,0.002853135,0.00000882934,0.00056614977],"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","domain_scores_codex":[0.996087,0.000121494355,0.0014070484,0.0006478138,0.0015592852,0.0001773231],"domain_scores_gemma":[0.9972259,0.00011895474,0.0010769411,0.00074020744,0.0007115687,0.00012647187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029340028,0.00020877543,0.0025176404,0.0016221266,0.0000493949,0.00014881346,0.0013759679,0.000047036305,0.000089414956],"category_scores_gemma":[0.0016498271,0.00013743548,0.0002848033,0.002371399,0.00015500568,0.0007626204,0.0010801195,0.00015442465,5.2107373e-7],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038762613,0.00018908276,0.013717621,0.881692,0.09310746,0.000055733803,0.000025981773,0.000008169808,5.0273076e-7,0.0028123064,0.0014105026,0.0069419052],"study_design_scores_gemma":[0.00030938172,0.00012193127,0.14218627,0.060584836,0.7872759,0.00025245885,0.0000068332843,0.006747284,1.1957675e-7,0.00032465818,0.001973335,0.0002169918],"about_ca_topic_score_codex":0.00012745467,"about_ca_topic_score_gemma":0.00013997228,"teacher_disagreement_score":0.82110715,"about_ca_system_score_codex":0.00029032465,"about_ca_system_score_gemma":0.00027129936,"threshold_uncertainty_score":0.5604456},"labels":[],"label_agreement":null},{"id":"W4400923706","doi":"10.23889/ijpds.v9i1.2370","title":"Public sector health analytics capacity before and after Covid-19: A case study of manager perspectives in New Brunswick, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; University of New Brunswick; Government of New Brunswick","funders":"","keywords":"Analytics; Business; Workforce; Surge Capacity; Promotion (chess); Public sector; Workforce planning; Public relations; Workforce development; Capacity building; Health care; Marketing; Medicine; Data science; Coronavirus disease 2019 (COVID-19); Politics; Political science; Computer science","score_opus":0.28338498131181217,"score_gpt":0.5304744255168906,"score_spread":0.24708944420507845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400923706","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9495234,0.00015092539,0.0016053648,0.04504266,0.002755769,0.0005971214,0.00028074012,0.000013509882,0.000030504385],"genre_scores_gemma":[0.99662375,0.000039350525,0.00054351694,0.0018409031,0.0006050331,0.000009244722,0.000052455765,0.000008715518,0.00027699955],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99771094,0.000164842,0.0007270771,0.00035253534,0.00066569995,0.00037888152],"domain_scores_gemma":[0.9981385,0.0002628396,0.00029744708,0.0002843628,0.00041474792,0.0006021007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029445507,0.000096128766,0.0001655408,0.00070957025,0.00061068666,0.00016137752,0.0005593834,0.000037868816,0.000103950406],"category_scores_gemma":[0.002000813,0.000082325576,0.000017185112,0.00066310336,0.0000749052,0.0015252413,0.00022410192,0.00035284192,7.222759e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042044714,0.00016509315,0.9030684,0.0002450677,0.000052709423,0.0001442524,0.048571005,0.00015029674,0.0000011914105,0.02232437,0.019052405,0.006183142],"study_design_scores_gemma":[0.0009350434,0.0001590027,0.8189545,0.00018017602,0.000014035549,0.000568487,0.10435085,0.03231318,7.037733e-8,0.001830559,0.04054343,0.00015064489],"about_ca_topic_score_codex":0.9462203,"about_ca_topic_score_gemma":0.9909154,"teacher_disagreement_score":0.084113896,"about_ca_system_score_codex":0.0024225216,"about_ca_system_score_gemma":0.032606393,"threshold_uncertainty_score":0.97287786},"labels":[],"label_agreement":null},{"id":"W4402390579","doi":"10.23889/ijpds.v9i5.2523","title":"Leveraging Linked Ontario’s Health-administrative Data to Evaluate Internet-delivered Cognitive Behavioural Therapy (iCBT) in routine care","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"The Internet; Cognition; Health care; Business; Psychology; Internet privacy; Computer science; Medicine; Psychiatry; World Wide Web; Political science","score_opus":0.3507822610327876,"score_gpt":0.4629413981844837,"score_spread":0.11215913715169612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390579","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97894204,0.00040240466,0.0045641507,0.009057957,0.0055888784,0.00080823567,0.00038477514,0.000083075895,0.00016846448],"genre_scores_gemma":[0.99491733,0.00001534685,0.000812479,0.00117183,0.00065179466,0.000017538523,0.002299684,0.000015772499,0.00009823565],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9975471,0.000024359575,0.0006596261,0.0006777503,0.00074959383,0.00034156378],"domain_scores_gemma":[0.9984302,0.000068995854,0.00027595958,0.00039453257,0.000782068,0.000048272814],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0022817878,0.00015488865,0.00018869678,0.00084619946,0.00024703937,0.0012693945,0.0022351067,0.000051031348,0.00007859019],"category_scores_gemma":[0.00057918316,0.00013689625,0.000033954977,0.000532113,0.000061817205,0.0045634075,0.0008961283,0.00033995853,0.000032758602],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028847408,0.00010528711,0.28389722,0.00008279495,0.00009129282,0.00012349569,0.004322056,0.000103405946,0.00014692792,0.009420554,0.0035557211,0.69786274],"study_design_scores_gemma":[0.0027554967,0.00022591803,0.6983535,0.0021405797,0.000034219018,0.0001693172,0.005103282,0.14723556,0.000026419639,0.0030081721,0.14028434,0.00066317804],"about_ca_topic_score_codex":0.15349254,"about_ca_topic_score_gemma":0.12779988,"teacher_disagreement_score":0.6971996,"about_ca_system_score_codex":0.0010062201,"about_ca_system_score_gemma":0.0007910435,"threshold_uncertainty_score":0.99976736},"labels":[],"label_agreement":null},{"id":"W4402390590","doi":"10.23889/ijpds.v9i5.2514","title":"Improving Cardiac Insights: Harnessing Privacy-Preserving Record Linkage (PPRL) to Obtain, Link, and Enhance Data for a Healthier Australia","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Victoria Park","funders":"","keywords":"Record linkage; Link (geometry); Linkage (software); Computer science; Data mining; Computer network; Medicine; Environmental health; Genetics; Biology; Gene","score_opus":0.35526995340542455,"score_gpt":0.5394998433459082,"score_spread":0.18422988994048362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390590","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06417964,0.00046615585,0.89300764,0.022269603,0.014528742,0.0009837556,0.004439086,0.00006538955,0.000059996706],"genre_scores_gemma":[0.76680976,0.00020695962,0.2223817,0.0015656053,0.003421169,0.000050532828,0.0024423092,0.000036258687,0.0030857187],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9949117,0.00011686367,0.0010994343,0.0013802277,0.0020994332,0.0003923971],"domain_scores_gemma":[0.99533534,0.0011233761,0.00042138898,0.0019277879,0.00089331093,0.00029877544],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.014527803,0.00016891168,0.0002455044,0.00083134556,0.0008053692,0.006721777,0.0087034255,0.000057635723,0.000041456096],"category_scores_gemma":[0.019698167,0.00013616067,0.000060308204,0.0008471148,0.00012606011,0.012206679,0.0054492173,0.00024527093,0.000029214436],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010583107,0.000033665747,0.0015281097,0.00009194818,0.000061461535,0.000010519184,0.00075568265,0.00020731206,0.001856756,0.0147260055,0.086471744,0.894151],"study_design_scores_gemma":[0.00018850491,0.00006371229,0.0049935346,0.0002715778,0.000027207287,0.000014305436,0.00035835162,0.23435855,0.000093529554,0.025393838,0.7340053,0.00023160432],"about_ca_topic_score_codex":0.00049560476,"about_ca_topic_score_gemma":0.00024808178,"teacher_disagreement_score":0.89391935,"about_ca_system_score_codex":0.00018742302,"about_ca_system_score_gemma":0.00026375699,"threshold_uncertainty_score":0.99665993},"labels":[],"label_agreement":null},{"id":"W4402390597","doi":"10.23889/ijpds.v9i5.2538","title":"Unravelling the Complexity of Homelessness: Investigating Reasons and Risk Factors for Chronic Homelessness","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Economic and Social Research Council","keywords":"Psychology","score_opus":0.21652098558380212,"score_gpt":0.4782289002004604,"score_spread":0.26170791461665827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390597","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9614125,0.0006042162,0.03171189,0.0005742472,0.0035396658,0.00050339755,0.0015960637,0.0000323169,0.000025713643],"genre_scores_gemma":[0.9965904,0.0004857663,0.0016659343,0.00001204613,0.000872044,0.000028330425,0.00029932967,0.000016994127,0.000029180032],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99799925,0.00013065973,0.0006170275,0.00033547136,0.00060857803,0.00030902866],"domain_scores_gemma":[0.99704444,0.0013734171,0.0004963405,0.00026337593,0.00071175094,0.00011068289],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003161821,0.00012322918,0.00027040206,0.00021546475,0.0020295398,0.00026412145,0.0012224265,0.00006976596,0.000023207811],"category_scores_gemma":[0.0017723014,0.00008309995,0.00006014526,0.0003519915,0.000639754,0.0013166763,0.00032275156,0.00036586125,0.0000014464256],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050304443,0.000042243748,0.6046317,0.0005102397,0.0001964688,0.0000016169813,0.035757966,0.000806173,0.0007609623,0.30988717,0.00010515223,0.047250003],"study_design_scores_gemma":[0.00097004697,0.0001046882,0.536261,0.0016441232,0.00014898193,0.0000033578779,0.0714128,0.27866536,0.00028256985,0.10393371,0.006184475,0.00038883946],"about_ca_topic_score_codex":0.0020580345,"about_ca_topic_score_gemma":0.003765908,"teacher_disagreement_score":0.2778592,"about_ca_system_score_codex":0.00021979304,"about_ca_system_score_gemma":0.0005471071,"threshold_uncertainty_score":0.99926966},"labels":[],"label_agreement":null},{"id":"W4402390607","doi":"10.23889/ijpds.v9i5.2576","title":"Linking Community-based Substance Use Disorder Treatment to Health Administrative Data: understanding vulnerable populations.","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Substance Abuse Treatment and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Substance use; Psychiatry; Psychology; Medicine; Environmental health","score_opus":0.5420710344422,"score_gpt":0.5098811437975593,"score_spread":0.03218989064464062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390607","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6038247,0.00064270804,0.36993492,0.01699991,0.00548288,0.00128347,0.0015567922,0.00019119229,0.000083429135],"genre_scores_gemma":[0.9620277,0.00008675582,0.029126981,0.0008347191,0.00028323143,0.0000133443455,0.007335054,0.000020809053,0.00027139598],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978837,0.000090056055,0.00047799115,0.00044869672,0.0008024454,0.00029715284],"domain_scores_gemma":[0.99808407,0.00043545617,0.00015944286,0.00085182034,0.00023948227,0.00022970623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016068324,0.0001727194,0.00021629417,0.00053546746,0.0012428933,0.00087565975,0.0010031889,0.000031869764,0.000026584486],"category_scores_gemma":[0.00038357792,0.00013606121,0.000058221376,0.0006006022,0.00008583127,0.0034894636,0.00011375299,0.00026859948,0.000009316554],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088140584,0.0009582006,0.8845731,0.00008202391,0.0004952009,0.00014545288,0.0067730253,0.0062189396,0.00028957886,0.04253472,0.0073187402,0.049729593],"study_design_scores_gemma":[0.011009195,0.0027988255,0.36304975,0.0053545563,0.00056933716,0.0007477011,0.010081233,0.43373653,0.0003248155,0.01263718,0.15829754,0.0013933402],"about_ca_topic_score_codex":0.00047270098,"about_ca_topic_score_gemma":0.005471019,"teacher_disagreement_score":0.52152336,"about_ca_system_score_codex":0.0018371769,"about_ca_system_score_gemma":0.0007465049,"threshold_uncertainty_score":0.95594555},"labels":[],"label_agreement":null},{"id":"W4402390631","doi":"10.23889/ijpds.v9i5.2631","title":"A population-based repeated cross-sectional study using administrative health data to examine the impact of the COVID-19 pandemic on mental wellness in citizens of the Métis Nation of Ontario","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Métis National Council","funders":"","keywords":"Pandemic; Mental health; Coronavirus disease 2019 (COVID-19); Population; Cross-sectional study; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Environmental health; Psychology; Geography; Political science; Medicine; Psychiatry; Virology; Disease","score_opus":0.42152846419291806,"score_gpt":0.5704699572863283,"score_spread":0.14894149309341026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99141926,0.0000139580325,0.0003891433,0.0036535063,0.0018826342,0.0008230649,0.0017936653,0.0000056988374,0.000019079635],"genre_scores_gemma":[0.9992196,0.000003576367,0.00010430925,0.00031980046,0.00010593218,0.0000047675117,0.00017917086,0.000004765522,0.000058091136],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99684536,0.00031611088,0.0008212836,0.00029954128,0.0015105057,0.00020721003],"domain_scores_gemma":[0.9979647,0.0005900088,0.0005972446,0.0004545467,0.00028880598,0.0001047125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069439327,0.00008721529,0.00015120627,0.00023040324,0.0009146518,0.00021015725,0.002176617,0.000032995587,0.000054931304],"category_scores_gemma":[0.0030031619,0.000049475253,0.00007352966,0.0008008251,0.00024226568,0.0007637545,0.00029838222,0.00018946739,1.7729168e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008293845,0.00007959321,0.982173,0.000011735423,0.000018974546,3.221398e-7,0.0035111355,0.011685031,0.000026400137,0.002021405,0.00010220966,0.00028723816],"study_design_scores_gemma":[0.00031518986,0.000074815456,0.9849688,0.00011524378,0.0000055710484,0.000007643546,0.00077571016,0.012978819,0.0000073828073,0.0004283164,0.00027431233,0.00004824127],"about_ca_topic_score_codex":0.45057788,"about_ca_topic_score_gemma":0.3972262,"teacher_disagreement_score":0.05335165,"about_ca_system_score_codex":0.0029689928,"about_ca_system_score_gemma":0.0068284287,"threshold_uncertainty_score":0.99880195},"labels":[],"label_agreement":null},{"id":"W4402390682","doi":"10.23889/ijpds.v9i5.2669","title":"Using newly linked hospital and population data to identify opportunities to reduce harms from sedative-hypnotic prescribing at population scale","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Mental Health Treatment and Access","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"St. Michael's Hospital; Trillium Health Centre; Sunnybrook Health Science Centre; Sinai Health System; Institute of Health Services and Policy Research","funders":"","keywords":"Sedative/hypnotic; Sedative; Scale (ratio); Population; Medicine; Psychiatry; Psychology; Environmental health; Geography","score_opus":0.41472260122159965,"score_gpt":0.5320087975668627,"score_spread":0.11728619634526305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390682","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9756507,0.00020055095,0.008038337,0.002835427,0.009726475,0.000744408,0.0026996126,0.000056595112,0.000047865913],"genre_scores_gemma":[0.9764282,0.0000191386,0.012976791,0.0002947094,0.001060574,0.000016058197,0.008727404,0.000026615544,0.00045048664],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970563,0.00007490583,0.0006852968,0.00094606425,0.0008936364,0.00034380026],"domain_scores_gemma":[0.998394,0.00014172809,0.0002612287,0.00066486595,0.00021131853,0.00032687443],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011195852,0.00019480997,0.00018599626,0.00060797133,0.0007648583,0.0013091598,0.0016477864,0.000065812565,0.00021829698],"category_scores_gemma":[0.00024818396,0.00018412869,0.000033411343,0.0003078413,0.00005829126,0.0057064104,0.0011700533,0.00015351409,0.0000376782],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000929226,0.00041005926,0.49382314,0.00009239666,0.00035176918,0.00012880715,0.006656974,0.0020985133,0.010828992,0.004539105,0.0147365155,0.4654045],"study_design_scores_gemma":[0.00054544926,0.00009094016,0.9248257,0.00041803755,0.00007361845,0.00006408381,0.00050763047,0.069514886,0.00005617367,0.0012311646,0.002388205,0.0002840659],"about_ca_topic_score_codex":0.008931816,"about_ca_topic_score_gemma":0.0007115629,"teacher_disagreement_score":0.46512043,"about_ca_system_score_codex":0.00060683774,"about_ca_system_score_gemma":0.00006521163,"threshold_uncertainty_score":0.99972755},"labels":[],"label_agreement":null},{"id":"W4402390729","doi":"10.23889/ijpds.v5i5.1646","title":"Linked administrative data’s role in Victoria’s first social impact investment, journey to social inclusion, working to end chronic homelessness","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Community Development and Social Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Inclusion (mineral); Financial inclusion; Investment (military); Social enterprise; Sociology; Political science; Public relations; Public administration; Gender studies; Law; Financial services","score_opus":0.27139919293275233,"score_gpt":0.4264455282508123,"score_spread":0.15504633531805995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390729","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95052,0.00014467468,0.0061947717,0.034886114,0.0028033594,0.00063678133,0.0036997688,0.000033308177,0.0010812376],"genre_scores_gemma":[0.995082,0.00003123146,0.0011241974,0.001074391,0.0017577261,0.0000076161255,0.000888392,0.000014882422,0.000019530255],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99806595,0.000030759766,0.00075141725,0.00045840914,0.00033834536,0.0003551065],"domain_scores_gemma":[0.9987253,0.00007685272,0.00046718313,0.00026772806,0.0001787956,0.00028416901],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0019212378,0.00015536485,0.00029535082,0.00050386984,0.0014089099,0.00082994375,0.0038008222,0.00006607742,0.00014092424],"category_scores_gemma":[0.0013570582,0.00017283858,0.000059538186,0.0008813645,0.000061377046,0.0024162107,0.003125063,0.0002914407,0.000035241465],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010043761,0.000584171,0.6037212,0.0000309985,0.0004332235,0.000033210206,0.19148572,0.0026161221,0.0008139327,0.10793833,0.02443222,0.06690649],"study_design_scores_gemma":[0.0013172578,0.0001653758,0.8294317,0.000062028266,0.0000064672226,0.0000057991424,0.0012177904,0.016032064,0.000013027085,0.014038214,0.13721006,0.0005002316],"about_ca_topic_score_codex":0.000906594,"about_ca_topic_score_gemma":0.0045812754,"teacher_disagreement_score":0.22571047,"about_ca_system_score_codex":0.0013227216,"about_ca_system_score_gemma":0.00048632346,"threshold_uncertainty_score":0.9998911},"labels":[],"label_agreement":null},{"id":"W4402390735","doi":"10.23889/ijpds.v9i5.2524","title":"Navigating Indigenous Data Sovereignty: A Decolonizing Approach to Understanding Opioid Use Amongst First Nations in Manitoba","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"First Nations Health and Social Secretariat of Manitoba","funders":"","keywords":"Sovereignty; Indigenous; Political science; Law; Biology; Ecology","score_opus":0.18907698664232483,"score_gpt":0.42784890315190793,"score_spread":0.2387719165095831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390735","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8363544,0.00038203824,0.11746673,0.004043316,0.021996755,0.003517734,0.002353619,0.00024919663,0.0136362305],"genre_scores_gemma":[0.9819741,0.0007770782,0.014572497,0.00007098399,0.0012783948,0.000007370844,0.0011586092,0.000018351031,0.000142563],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968344,0.00008556499,0.0005649841,0.0006647552,0.0012939546,0.00055636326],"domain_scores_gemma":[0.99809456,0.000628466,0.00020196618,0.00049351976,0.00032969104,0.00025182316],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004539893,0.00013023445,0.00012825163,0.00065803254,0.009313447,0.0028678773,0.003251429,0.000077940655,0.000020473963],"category_scores_gemma":[0.0005898407,0.00012311693,0.000032546614,0.0014001334,0.00019285701,0.008261702,0.00008363618,0.00035856356,0.0000141092705],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018606816,0.0001588812,0.022123313,0.000043627806,0.00003229409,0.000013068661,0.12987152,0.0011728525,0.000003222739,0.84416837,0.00026571477,0.002128569],"study_design_scores_gemma":[0.0010410441,0.00013163663,0.045935713,0.0027121597,0.00008644696,0.00028770402,0.06711388,0.14053535,0.00002000263,0.08192198,0.6588134,0.0014006566],"about_ca_topic_score_codex":0.09181191,"about_ca_topic_score_gemma":0.7682178,"teacher_disagreement_score":0.7622464,"about_ca_system_score_codex":0.0027519013,"about_ca_system_score_gemma":0.0070847427,"threshold_uncertainty_score":0.99854416},"labels":[],"label_agreement":null},{"id":"W4402390737","doi":"10.23889/ijpds.v9i5.2518","title":"Leveraging Machine Learning to Combat Missingness and Error in Data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Victoria Park","funders":"","keywords":"Missing data; Computer science; Artificial intelligence; Machine learning","score_opus":0.11322706319805584,"score_gpt":0.41989037256053413,"score_spread":0.3066633093624783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390737","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02735101,0.00014994979,0.9639165,0.0072844485,0.000944985,0.00013688985,0.00006901108,0.0001004426,0.000046810223],"genre_scores_gemma":[0.90558577,0.00003143297,0.09381937,0.0001722111,0.00011777172,0.000005908751,0.000115445706,0.0000057452944,0.00014635127],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861634,0.000018131692,0.00026616588,0.0005299501,0.00041769297,0.00015174928],"domain_scores_gemma":[0.99912924,0.00007415366,0.00006987332,0.0005036864,0.00012514665,0.00009787617],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0014940385,0.000072570154,0.00006842954,0.0004941182,0.00032289873,0.0015467805,0.003404221,0.000018741235,0.0000066790767],"category_scores_gemma":[0.0002687286,0.00006696417,0.000012123284,0.00059152895,0.000041105162,0.003946093,0.0015568453,0.00017514318,0.000004640075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001873643,0.00006321211,0.011772387,0.000021091562,0.000021403344,0.000032653155,0.0009086651,0.0032160778,0.0044852355,0.06700683,0.002832877,0.9096208],"study_design_scores_gemma":[0.0000786767,0.000014357688,0.008179114,0.00006392325,0.0000020811299,0.00015989997,0.000027189433,0.92405707,0.00008999627,0.0033231052,0.06391559,0.00008902024],"about_ca_topic_score_codex":0.00016445224,"about_ca_topic_score_gemma":0.00004878252,"teacher_disagreement_score":0.920841,"about_ca_system_score_codex":0.00009151742,"about_ca_system_score_gemma":0.00009586851,"threshold_uncertainty_score":0.9994897},"labels":[],"label_agreement":null},{"id":"W4402390755","doi":"10.23889/ijpds.v9i5.2639","title":"Early life child protection contacts and developmental risk at age five: a whole-of-population cohort study of 479,413 children in two Australian states.","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child Abuse and Trauma","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Cohort; Cohort study; Population; Child protection; Medicine; Demography; Pediatrics; Environmental health; Sociology","score_opus":0.04759899983661832,"score_gpt":0.38619076489535215,"score_spread":0.33859176505873384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390755","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99715513,0.000045269717,0.00019330531,0.00018343965,0.0010089,0.00087379257,0.00046045906,0.000016873235,0.00006282947],"genre_scores_gemma":[0.99887824,0.000016437622,0.00025629613,0.00001842374,0.00014714432,0.00001811794,0.000534141,0.000011369929,0.00011982245],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980067,0.000071739916,0.00066404784,0.00044839742,0.0006362324,0.00017289078],"domain_scores_gemma":[0.9991745,0.00006159604,0.0003433026,0.00020008117,0.0001311772,0.00008934704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011929818,0.000120887904,0.00017543485,0.0005759848,0.00019408783,0.0001762709,0.00052211515,0.00003494921,0.00007304128],"category_scores_gemma":[0.0001976216,0.00011063518,0.00003279686,0.00035589482,0.00007759435,0.0012474777,0.00016449962,0.00022537766,0.000007488328],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000166121,0.0001910726,0.9884632,0.000005852653,0.00014508357,0.000011389421,0.002394361,0.00042960333,0.0001147264,0.00032725537,0.00014692293,0.007604418],"study_design_scores_gemma":[0.001464329,0.00013675628,0.9954025,0.00011711729,0.000036178768,0.00012550982,0.00031214242,0.0017711162,0.000022247925,0.00031914693,0.00018337318,0.000109541565],"about_ca_topic_score_codex":0.011932478,"about_ca_topic_score_gemma":0.0033108874,"teacher_disagreement_score":0.008621591,"about_ca_system_score_codex":0.00018082623,"about_ca_system_score_gemma":0.000044741413,"threshold_uncertainty_score":0.99464715},"labels":[],"label_agreement":null},{"id":"W4402390774","doi":"10.23889/ijpds.v9i5.2837","title":"Prevalence of a dual diagnosis of mental illness and substance use disorder in Ontario, Canada: a retrospective cohort study using linked administrative data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Substance Abuse Treatment and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Centre for Addiction and Mental Health; Centre for Global Health Research","funders":"","keywords":"Dual diagnosis; Mental illness; Retrospective cohort study; Substance use; Medicine; Cohort; Psychiatry; Substance abuse; Dual (grammatical number); Mental health; Internal medicine","score_opus":0.11892585899477821,"score_gpt":0.39725760971515894,"score_spread":0.27833175072038074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390774","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975786,0.00019694114,0.000110315625,0.00009031202,0.00070177496,0.00059541146,0.0007190418,0.0000038571184,0.000003738021],"genre_scores_gemma":[0.9985446,0.00009421767,0.0009976341,0.000009903794,0.00003124867,0.000009137122,0.0002467094,0.0000058015353,0.000060764567],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99818873,0.000019938214,0.0004150676,0.00038211432,0.00087882683,0.00011531011],"domain_scores_gemma":[0.99899244,0.00014971588,0.00018793515,0.00032746766,0.0002879962,0.000054444365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006378423,0.000093552575,0.00019724251,0.00019939458,0.00008265138,0.00007016332,0.0004555881,0.000017223458,0.00004424877],"category_scores_gemma":[0.00038510902,0.000076218945,0.00001714117,0.00026045096,0.00012590087,0.0020524636,0.00014809985,0.00011755559,5.149843e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015459873,0.0001468639,0.99739456,0.000011341819,0.00011127947,0.000045532885,0.0015267716,0.000016463162,0.00006160053,0.00010110322,0.0000502489,0.00037965216],"study_design_scores_gemma":[0.00088127627,0.00009592597,0.99027836,0.00035306043,0.00010156631,0.00006263848,0.00087901973,0.007146926,0.000060420924,0.000041041076,0.000028836977,0.0000709089],"about_ca_topic_score_codex":0.4183209,"about_ca_topic_score_gemma":0.9455244,"teacher_disagreement_score":0.5272035,"about_ca_system_score_codex":0.0007817627,"about_ca_system_score_gemma":0.0010043145,"threshold_uncertainty_score":0.5855526},"labels":[],"label_agreement":null},{"id":"W4402390793","doi":"10.23889/ijpds.v9i5.2810","title":"Trends in Pregnancy-Associated Opioid Toxicity and Mortality","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Prenatal Substance Exposure Effects","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Pregnancy; Opioid; Medicine; Toxicity; Obstetrics; Internal medicine; Biology","score_opus":0.06105157347050769,"score_gpt":0.40643983017613833,"score_spread":0.3453882567056306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390793","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941379,0.0008086412,0.0013337279,0.0007486023,0.002340034,0.0001508535,0.00025261674,0.000039605264,0.00018802477],"genre_scores_gemma":[0.9983147,0.00005865482,0.0007922928,0.00006738938,0.00017818247,0.0000052604287,0.00042369106,0.000006999479,0.0001528456],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99849606,0.000019830948,0.00028914615,0.00033207468,0.00069008983,0.0001728192],"domain_scores_gemma":[0.9993829,0.0000765659,0.000079675556,0.00020266708,0.00015194906,0.0001062343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010940618,0.00008029088,0.00011713934,0.0004974251,0.00008599456,0.0002572655,0.00045740933,0.000038070513,0.000030385096],"category_scores_gemma":[0.00086334784,0.0000679355,0.000032948366,0.0005029683,0.0000878353,0.0019011492,0.00015816343,0.000178951,0.000002025512],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012629315,0.00024916363,0.7123281,0.000058514837,0.00012814841,0.00028934068,0.00038064743,0.000061121,0.013743704,0.0051729246,0.0015774887,0.26588458],"study_design_scores_gemma":[0.0006869689,0.000066925466,0.94386077,0.0007343456,0.00002032546,0.00015616493,0.000009528185,0.051659063,0.00053213193,0.0016648407,0.0005235125,0.00008540608],"about_ca_topic_score_codex":0.000088427034,"about_ca_topic_score_gemma":0.00028511966,"teacher_disagreement_score":0.26579916,"about_ca_system_score_codex":0.00028949082,"about_ca_system_score_gemma":0.00011378789,"threshold_uncertainty_score":0.2770329},"labels":[],"label_agreement":null},{"id":"W4402390804","doi":"10.23889/ijpds.v9i5.2795","title":"Risk of death after type of intimate partner violence (IPV) involvement","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Intimate Partner and Family Violence","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Domestic violence; Psychology; Medical emergency; Computer security; Social psychology; Medicine; Computer science; Poison control; Human factors and ergonomics","score_opus":0.09089297550018266,"score_gpt":0.4425134868825764,"score_spread":0.35162051138239375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390804","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94982904,0.0012114109,0.029088002,0.00025062182,0.012278829,0.0005186818,0.0011911542,0.00006347702,0.005568756],"genre_scores_gemma":[0.9942796,0.00092926214,0.0043365047,0.000043434622,0.0002640631,0.000005330558,0.00005225186,0.0000063455464,0.000083158004],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9978308,0.000058439182,0.00047683573,0.00027892363,0.0011358766,0.00021911947],"domain_scores_gemma":[0.9983207,0.00012125971,0.00025716153,0.000257119,0.00095469103,0.000089060646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030066168,0.00008226059,0.00011821463,0.00030166178,0.00024564515,0.00023616577,0.0015044443,0.000037221966,0.00012689087],"category_scores_gemma":[0.0007529643,0.0000692407,0.00006085814,0.00038418738,0.00036984016,0.0018844065,0.00023969522,0.00011857585,0.000013570236],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031043668,0.0001852145,0.37305316,0.00009072408,0.00017852837,0.000017096838,0.0035788887,0.001333513,0.002666628,0.5513254,0.0015739684,0.06568642],"study_design_scores_gemma":[0.00050459814,0.00021104085,0.792271,0.0017508405,0.00015005328,0.000019709763,0.001112267,0.087802425,0.0021369667,0.0827536,0.030827848,0.00045965295],"about_ca_topic_score_codex":0.0012186443,"about_ca_topic_score_gemma":0.000051320065,"teacher_disagreement_score":0.4685718,"about_ca_system_score_codex":0.00012280575,"about_ca_system_score_gemma":0.00037584838,"threshold_uncertainty_score":0.28235537},"labels":[],"label_agreement":null},{"id":"W4402390868","doi":"10.23889/ijpds.v9i5.2790","title":"Associations between long-term exposures to environmental factors and the development of amyotrophic lateral sclerosis: A matched case-control study","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Amyotrophic Lateral Sclerosis Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Stan Cassidy Foundation; University of New Brunswick; Université de Sherbrooke","funders":"","keywords":"Amyotrophic lateral sclerosis; Term (time); Environmental health; Environmental science; Medicine; Disease; Internal medicine","score_opus":0.10954125740411312,"score_gpt":0.39309095015745193,"score_spread":0.2835496927533388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9944377,0.00006116755,0.002363039,0.0011822011,0.00039605043,0.0007876972,0.0007552286,0.000014623219,0.0000023028845],"genre_scores_gemma":[0.99849564,0.00001051707,0.0009746621,0.000041571915,0.00021845436,0.00001792619,0.00019406146,0.000011802462,0.000035349676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975816,0.00007051511,0.0006073062,0.00032580146,0.0012033398,0.00021145186],"domain_scores_gemma":[0.99906576,0.0002421064,0.00014705742,0.00023807095,0.00014192975,0.00016506483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019745931,0.000117283744,0.00022846262,0.0003181527,0.00039957033,0.0004017986,0.00062777323,0.000031583906,0.000042729775],"category_scores_gemma":[0.00035957567,0.000071040595,0.000053004638,0.00020669357,0.00016580586,0.00081592635,0.0003327373,0.00018621217,0.000003788474],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013049248,0.0000747433,0.98465085,0.0000064724495,0.00027263907,0.00002944915,0.002081302,0.000026013271,0.0035844543,0.00004512542,0.000019839968,0.009078594],"study_design_scores_gemma":[0.0015305091,0.00011376024,0.99635816,0.0001006565,0.000085851476,0.00010547525,0.00014057504,0.0013163644,0.00010361925,0.00006068342,0.000011377524,0.00007296036],"about_ca_topic_score_codex":0.000108921166,"about_ca_topic_score_gemma":0.000088617904,"teacher_disagreement_score":0.011707293,"about_ca_system_score_codex":0.0003260885,"about_ca_system_score_gemma":0.00015339501,"threshold_uncertainty_score":0.3874553},"labels":[],"label_agreement":null},{"id":"W4402390917","doi":"10.23889/ijpds.v9i5.2858","title":"Examining The Care Pathways Patients Experience When Accessing Outpatient Psychiatric Care in British Columbia","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University; University of British Columbia; Dalhousie University; Ontario Shores Centre for Mental Health Sciences; University of Toronto","funders":"","keywords":"Psychiatry; Psychology; Medicine","score_opus":0.27726320686672346,"score_gpt":0.5034064651155912,"score_spread":0.22614325824886772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390917","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.990207,0.0004917116,0.0018985067,0.00063098146,0.0058239107,0.00050767174,0.0003398924,0.000028011878,0.00007230845],"genre_scores_gemma":[0.99172264,0.000056700217,0.0059135174,0.00048533818,0.00055795995,0.000021753984,0.0012018296,0.00001463823,0.000025600048],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99703187,0.00004984873,0.0009321237,0.00047787337,0.0012851772,0.00022309819],"domain_scores_gemma":[0.9978982,0.00030193327,0.0002930199,0.00032835823,0.0010767808,0.000101699785],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011315276,0.000081475926,0.00011884446,0.00020990596,0.00044022585,0.0023330497,0.0010308033,0.000040457602,0.00008386366],"category_scores_gemma":[0.0039013296,0.000086328866,0.00004777559,0.0004306122,0.000099027435,0.0032870993,0.0003466059,0.00030653906,0.00000425131],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029823626,0.00003892116,0.66483647,0.000021555086,0.000008458,0.000014293723,0.002714514,0.00006496079,0.000026285608,0.000016482209,0.0011627479,0.3310655],"study_design_scores_gemma":[0.0011697945,0.00020746092,0.9625806,0.00042713984,0.00004290305,0.00011001049,0.011378761,0.011996658,0.00000541183,0.00033081527,0.01161212,0.0001382765],"about_ca_topic_score_codex":0.004742344,"about_ca_topic_score_gemma":0.01572802,"teacher_disagreement_score":0.33092722,"about_ca_system_score_codex":0.00057637267,"about_ca_system_score_gemma":0.0004715282,"threshold_uncertainty_score":0.99870265},"labels":[],"label_agreement":null},{"id":"W4402390933","doi":"10.23889/ijpds.v9i5.2791","title":"Comparing Methods for Missing Paternal Linkages in Administrative Data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Missing data; Computer science; Business; Econometrics; Data science; Economics; Machine learning","score_opus":0.5449343392520652,"score_gpt":0.6110982106633693,"score_spread":0.06616387141130409,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390933","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07688923,0.0015436335,0.8853327,0.01392448,0.017851492,0.00066191965,0.0014872401,0.00012323684,0.002186047],"genre_scores_gemma":[0.89779943,0.00013003474,0.100677796,0.000051719817,0.0007374887,0.0000067428764,0.000445729,0.0000062218,0.00014484505],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981193,0.00011631505,0.00040762904,0.00044659778,0.0006298424,0.00028034084],"domain_scores_gemma":[0.9986353,0.0005311552,0.00014549142,0.00030958987,0.0002541939,0.00012427347],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007292946,0.00008977364,0.00012212555,0.0004653329,0.00064278004,0.0020034593,0.0033988927,0.0000422908,0.000031771477],"category_scores_gemma":[0.0012739141,0.00007854313,0.000040776595,0.000449405,0.00024681416,0.0041781287,0.0003703457,0.00016509775,0.0000013963365],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003574774,0.00005416558,0.06512314,0.000015411062,0.000059860187,0.000006356958,0.0038453422,0.00008714737,0.0001940926,0.051587503,0.0014358438,0.8775554],"study_design_scores_gemma":[0.00065993564,0.000085332584,0.18035194,0.00048827028,0.000046723973,0.000044148357,0.0038167017,0.42366675,0.000063314095,0.11987017,0.27050814,0.000398581],"about_ca_topic_score_codex":0.0008128978,"about_ca_topic_score_gemma":0.0024106468,"teacher_disagreement_score":0.8771568,"about_ca_system_score_codex":0.00012314794,"about_ca_system_score_gemma":0.00059144694,"threshold_uncertainty_score":0.99903256},"labels":[],"label_agreement":null},{"id":"W4402390973","doi":"10.23889/ijpds.v9i5.2813","title":"The CanPath-HDRN Canada Collaboration: Enabling Multi-jurisdictional Research in Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Environmental resource management; Environmental science","score_opus":0.6074584620630169,"score_gpt":0.5617156114665115,"score_spread":0.0457428505965054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390973","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39218712,0.01066772,0.016617063,0.49939162,0.06628865,0.0019770274,0.011851669,0.00005302957,0.000966117],"genre_scores_gemma":[0.99524903,0.00021812528,0.0014079094,0.0013052776,0.0010784209,0.000029410912,0.00026362218,0.000014324837,0.00043389422],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9958872,0.00015492324,0.0021729677,0.0005256099,0.000830754,0.0004285242],"domain_scores_gemma":[0.9964469,0.0017486906,0.00055506977,0.00040278936,0.00067400374,0.00017254509],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.027964812,0.000097580756,0.0001979294,0.00052171474,0.0010689426,0.0011484504,0.0017403911,0.000032671018,0.000062559135],"category_scores_gemma":[0.005239175,0.00009649909,0.00002389215,0.0008116462,0.000097127464,0.0023341773,0.00018519752,0.0003397671,0.000024233575],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.0000653206,0.000060370185,0.18674389,0.00010123567,0.0001359581,0.000054121414,0.0011867104,0.021044977,0.000019837105,0.427939,0.3559403,0.0067082695],"study_design_scores_gemma":[0.00034090894,0.000011727252,0.05427374,0.000121999095,0.000001591656,0.000044183907,0.002123769,0.406755,0.0000039440306,0.008440075,0.52771324,0.00016980605],"about_ca_topic_score_codex":0.9882491,"about_ca_topic_score_gemma":0.99889123,"teacher_disagreement_score":0.6030619,"about_ca_system_score_codex":0.009789698,"about_ca_system_score_gemma":0.018534513,"threshold_uncertainty_score":0.9998885},"labels":[],"label_agreement":null},{"id":"W4402390999","doi":"10.23889/ijpds.v9i5.2505","title":"Pragmatic Clinical Trials, Linkages and Agreements: Interjurisdictional Collaboration on Pragmatic Clinical Trials","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Alberta Health Services","funders":"","keywords":"Clinical trial; Computer science; Medicine; Internal medicine","score_opus":0.7759987835642644,"score_gpt":0.6766258612480722,"score_spread":0.09937292231619221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402390999","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23338872,0.005008165,0.35544097,0.2754569,0.10540285,0.0062205633,0.017263055,0.00027950827,0.0015392575],"genre_scores_gemma":[0.93852067,0.0024241444,0.031516604,0.010425791,0.012986669,0.00016753498,0.0029370815,0.000069157875,0.00095237076],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9813409,0.002993129,0.013682101,0.0010260884,0.00064928475,0.00030853352],"domain_scores_gemma":[0.97061837,0.020797456,0.0068710875,0.0006931296,0.0006173083,0.00040265868],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.33605587,0.00021066648,0.0013067169,0.0009834813,0.0004567027,0.0019978564,0.0012270658,0.0001741671,0.0003206759],"category_scores_gemma":[0.21989904,0.00019977307,0.00027194904,0.00037324885,0.00023608023,0.004363778,0.0002246034,0.0004854419,0.0003385538],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003264109,0.00067632383,0.07619519,0.00035844656,0.0012560913,0.000011162009,0.0011497037,0.0008532514,0.000019140607,0.57663184,0.27337262,0.06914983],"study_design_scores_gemma":[0.0032309867,0.00050485646,0.07179094,0.0010539922,0.000104022656,0.0000849763,0.0006842834,0.54532975,0.000002290188,0.10706665,0.26963997,0.00050730014],"about_ca_topic_score_codex":0.00006238097,"about_ca_topic_score_gemma":0.000044122615,"teacher_disagreement_score":0.70513195,"about_ca_system_score_codex":0.0005467812,"about_ca_system_score_gemma":0.0006806031,"threshold_uncertainty_score":0.99903816},"labels":[],"label_agreement":null},{"id":"W4402391020","doi":"10.23889/ijpds.v9i5.2856","title":"Co-Creating an Inclusion, Diversity, Equity, and Accessibility Strategy: Defining approach and outcomes in a health data research network","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health","funders":"","keywords":"Equity (law); Inclusion (mineral); Diversity (politics); Health equity; Business; Data science; Computer science; Knowledge management; Psychology; Sociology; Economic growth; Health care; Political science; Economics; Social psychology","score_opus":0.3759531843871176,"score_gpt":0.5339225214879914,"score_spread":0.15796933710087374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391020","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97533745,0.001240697,0.008495026,0.0108433105,0.001599344,0.0007105168,0.000372961,0.000113484195,0.0012871978],"genre_scores_gemma":[0.99635834,0.000052680316,0.00232386,0.0002634791,0.0003989374,0.000002517791,0.0005844708,0.000006614851,0.0000091203],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99756503,0.000049360875,0.00045009924,0.00059297186,0.0009879794,0.0003545852],"domain_scores_gemma":[0.9989667,0.00013844209,0.00018522712,0.00040027723,0.00026552845,0.000043840828],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.019573748,0.00008269733,0.00015012635,0.0006416355,0.002233522,0.0022700413,0.0025544572,0.00004621765,0.000005696259],"category_scores_gemma":[0.0009722756,0.000069302856,0.0000088776715,0.0005918155,0.00016372895,0.008193073,0.028498909,0.00031076692,0.0000011843281],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014316685,0.000031056516,0.70517576,0.00013755856,0.00000836831,0.000006452072,0.00012437878,0.0000847402,0.000005598036,0.09637421,0.0003801788,0.19765735],"study_design_scores_gemma":[0.00027597728,0.000023824563,0.41031379,0.0002343139,0.0000037332138,0.000038389408,0.00049536384,0.4938728,1.5127819e-7,0.09038187,0.00424789,0.00011192115],"about_ca_topic_score_codex":0.018078642,"about_ca_topic_score_gemma":0.004751126,"teacher_disagreement_score":0.49378803,"about_ca_system_score_codex":0.00013866236,"about_ca_system_score_gemma":0.00020110302,"threshold_uncertainty_score":0.99906546},"labels":[],"label_agreement":null},{"id":"W4402391084","doi":"10.23889/ijpds.v9i5.2585","title":"Timely data on the dynamic drug supply is crucial in addressing the ongoing drug poisoning crisis. The team is exploring ways to share information with emergency responders, healthcare providers, government officials, and pwSUD.","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Red Deer Polytechnic; Alberta Health Services","funders":"","keywords":"Government (linguistics); Drug; Business; Health care; Public relations; Medical emergency; Medicine; Knowledge management; Internet privacy; Political science; Computer science; Pharmacology; Economics; Economic growth","score_opus":0.33544122424321887,"score_gpt":0.46917311325209016,"score_spread":0.13373188900887129,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391084","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61643666,0.0005124071,0.002114619,0.37581766,0.001998885,0.0013184242,0.0016642429,0.000027415826,0.000109679815],"genre_scores_gemma":[0.9927713,0.00023529479,0.0005550883,0.005925864,0.00021135519,0.00002010409,0.00023076816,0.000010673353,0.000039524562],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972789,0.00006399534,0.0004963912,0.0003318959,0.0015957591,0.00023300799],"domain_scores_gemma":[0.9985877,0.0004214312,0.00023811914,0.0004896332,0.00015976532,0.000103311904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028204645,0.0001288848,0.00011222649,0.00016549832,0.000736876,0.00085349067,0.0012722423,0.000015809705,0.00005779877],"category_scores_gemma":[0.0011828193,0.000064508145,0.000027810791,0.0003955445,0.00005680062,0.005285233,0.0005547806,0.00044399482,0.000007180794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006031878,0.00032390593,0.21987271,0.00065728836,0.00056480186,0.000057874036,0.09641794,0.0034554442,0.0005802115,0.023782557,0.29761672,0.3506387],"study_design_scores_gemma":[0.0010511897,0.0001954315,0.10814481,0.0026772094,0.00013877492,0.00021462998,0.022198504,0.7454627,0.00019689424,0.0010239468,0.118343584,0.00035232614],"about_ca_topic_score_codex":0.00051768305,"about_ca_topic_score_gemma":0.0004061833,"teacher_disagreement_score":0.74200726,"about_ca_system_score_codex":0.00031925333,"about_ca_system_score_gemma":0.00023607191,"threshold_uncertainty_score":0.823023},"labels":[],"label_agreement":null},{"id":"W4402391085","doi":"10.23889/ijpds.v9i5.2801","title":"Using Polars to Improve String Similarity Performance in Python","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Python (programming language); Computer science; String (physics); Similarity (geometry); Programming language; Physics; Artificial intelligence; Theoretical physics","score_opus":0.10142318949889507,"score_gpt":0.41633512492248737,"score_spread":0.3149119354235923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391085","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16784339,0.00006351312,0.82483894,0.0007903174,0.0061053224,0.00014311475,0.00013722235,0.000047301568,0.000030874304],"genre_scores_gemma":[0.82388914,0.00001788292,0.175548,0.00014448196,0.00032800314,0.000002262013,0.000042113308,0.000006101169,0.000021997983],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980227,0.00001676664,0.00034658308,0.0005250669,0.000830217,0.0002587138],"domain_scores_gemma":[0.9990532,0.000055473305,0.00008518447,0.00047740526,0.00022114096,0.00010761367],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0016414232,0.00009470329,0.00008423843,0.0006328901,0.00027090442,0.0016730628,0.003527741,0.000028355505,0.0000052482765],"category_scores_gemma":[0.00025530628,0.00008369382,0.000026774915,0.00069444627,0.000030391664,0.009709829,0.0013934935,0.00019347126,0.0000065926274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005882229,0.0001086567,0.031002404,0.000041656083,0.000028398952,0.00008430884,0.0005233824,0.0375398,0.024446107,0.055317473,0.0010622322,0.84978676],"study_design_scores_gemma":[0.00012667873,0.000027263288,0.02671529,0.00015700534,0.0000019060398,0.00008231551,0.0000076219108,0.9625881,0.00044856462,0.0014633889,0.008268547,0.000113362476],"about_ca_topic_score_codex":0.0001435648,"about_ca_topic_score_gemma":0.000021647733,"teacher_disagreement_score":0.92504823,"about_ca_system_score_codex":0.0002962203,"about_ca_system_score_gemma":0.00024503184,"threshold_uncertainty_score":0.9993633},"labels":[],"label_agreement":null},{"id":"W4402391095","doi":"10.23889/ijpds.v9i5.2620","title":"Co-creating a Data Asset Inventory for Equity-Oriented Research","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"","keywords":"Equity (law); Business; Asset (computer security); Finance; Computer science; Political science","score_opus":0.47785924052836104,"score_gpt":0.6345003351142309,"score_spread":0.15664109458586983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391095","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11840721,0.001422413,0.7323355,0.035629746,0.03250658,0.003166704,0.041548602,0.00047622877,0.034506995],"genre_scores_gemma":[0.96585685,0.00019876788,0.018176265,0.000146629,0.0038213648,0.00002028305,0.010134449,0.000019400173,0.0016259956],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9958578,0.00016249708,0.0004340811,0.0006417425,0.0024362924,0.00046761354],"domain_scores_gemma":[0.9973191,0.000854296,0.0001500606,0.00066689536,0.0008070395,0.00020261075],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.023884594,0.0000809951,0.00010948871,0.00072451704,0.002587056,0.0031172598,0.0060333437,0.000033183216,0.00008925228],"category_scores_gemma":[0.010366982,0.00007345398,0.00005479673,0.00077346177,0.00044477673,0.007209094,0.0013306135,0.0002530837,0.000015921934],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000071816685,0.00012344006,0.011698386,0.000043788776,0.00017917634,0.000018546243,0.0035794103,0.00013854087,0.0026291003,0.5405035,0.15976897,0.28124535],"study_design_scores_gemma":[0.00015236864,0.000024011311,0.0009613683,0.00016523554,0.00002105265,0.000009086572,0.0012355177,0.21706828,0.000021805805,0.012812125,0.7674157,0.00011346259],"about_ca_topic_score_codex":0.001235297,"about_ca_topic_score_gemma":0.0014742838,"teacher_disagreement_score":0.84744966,"about_ca_system_score_codex":0.00033837638,"about_ca_system_score_gemma":0.0010021,"threshold_uncertainty_score":0.99934447},"labels":[],"label_agreement":null},{"id":"W4402391115","doi":"10.23889/ijpds.v9i5.2502","title":"Development of a dictionary of information items inspired by common data models to support health research data access requests","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Sherbrooke; Canadian Institute for Health Information","funders":"","keywords":"Computer science; Data access; Data science; Data mining; Information retrieval; Database","score_opus":0.8228812729718443,"score_gpt":0.6533858271484233,"score_spread":0.16949544582342102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391115","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030685231,0.00016879763,0.9033162,0.012239527,0.00492567,0.0010450883,0.046997774,0.000043877026,0.0005778159],"genre_scores_gemma":[0.9092532,0.00012264522,0.049879048,0.00054868055,0.0001602007,0.000011163397,0.039861135,0.000009454456,0.00015451778],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9904437,0.00017634165,0.0021320616,0.0007243376,0.006231599,0.00029197862],"domain_scores_gemma":[0.9942442,0.0005998697,0.0007220942,0.0026757321,0.0015377282,0.00022035433],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.045107204,0.00010497393,0.00022407569,0.0017129019,0.0004478292,0.002046943,0.020691669,0.00003391594,0.000053190543],"category_scores_gemma":[0.004072517,0.00008639069,0.000022338545,0.0017687244,0.00018621505,0.037062112,0.011512933,0.00019637724,0.00002805925],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009869539,0.00011479223,0.0007033988,0.00004784731,0.00004573679,0.0000015711139,0.0012019769,0.0013041905,0.0001621474,0.019060122,0.41191626,0.56534326],"study_design_scores_gemma":[0.00022893054,0.000086923064,0.0046581617,0.00022590796,0.000006021518,0.000018958335,0.0006804635,0.36384434,0.00008443063,0.015297875,0.61474353,0.00012442686],"about_ca_topic_score_codex":0.0008483648,"about_ca_topic_score_gemma":0.00064554205,"teacher_disagreement_score":0.87856793,"about_ca_system_score_codex":0.00025242154,"about_ca_system_score_gemma":0.0015090227,"threshold_uncertainty_score":0.99898905},"labels":[],"label_agreement":null},{"id":"W4402391160","doi":"10.23889/ijpds.v9i5.2501","title":"Development of a framework to facilitate a data assembly plan for multi-regional research","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Sherbrooke; Canadian Institute for Health Information","funders":"","keywords":"Plan (archaeology); Computer science; Process management; Data science; Business; Geography","score_opus":0.640787032152144,"score_gpt":0.5244936683058173,"score_spread":0.11629336384632671,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391160","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010224628,0.00008207554,0.98316747,0.0016241322,0.0033999865,0.00033621985,0.0011081025,0.000042036754,0.000015368298],"genre_scores_gemma":[0.37718108,0.000002299565,0.6217129,0.00005256902,0.00026495577,0.000012781815,0.00067296304,0.0000053178373,0.00009512585],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966953,0.00004751679,0.0005950249,0.0007296686,0.0015908392,0.00034164166],"domain_scores_gemma":[0.9971847,0.00054848474,0.00013237867,0.0009059377,0.0010600718,0.0001684067],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.007401685,0.00010163404,0.00012647748,0.000613707,0.00046688755,0.0013515056,0.009651089,0.00004005623,0.0000026777573],"category_scores_gemma":[0.0015770582,0.00008831379,0.000036309106,0.00078516925,0.000069096925,0.002501582,0.0019807594,0.00018783222,0.000017819038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020447835,0.0003793159,0.0017004554,0.00022222941,0.00031564003,0.000028885734,0.010053518,0.010308918,0.004555351,0.46225122,0.08196073,0.42801926],"study_design_scores_gemma":[0.00016392232,0.000038710412,0.0020439038,0.00035376154,0.0000023413575,0.00006158502,0.000063285326,0.77542645,0.00004725828,0.0029903383,0.21869583,0.00011259652],"about_ca_topic_score_codex":0.000051134306,"about_ca_topic_score_gemma":0.00004370335,"teacher_disagreement_score":0.7651175,"about_ca_system_score_codex":0.00016411798,"about_ca_system_score_gemma":0.0009113816,"threshold_uncertainty_score":0.99968517},"labels":[],"label_agreement":null},{"id":"W4402391181","doi":"10.23889/ijpds.v9i5.2633","title":"Enhancing Disease Detection in Electronic Medical Records: Integrating Human Expertise and Large Language Models with Application to Diabetes, Hypertension, and Acute Myocardial Infarction","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; Libin Cardiovascular Institute of Alberta; University of Calgary","funders":"","keywords":"Myocardial infarction; Diabetes mellitus; Disease; Medicine; Electronic medical record; Medical record; Cardiology; Internal medicine; Intensive care medicine; Medical emergency","score_opus":0.014779285057601788,"score_gpt":0.34676686787569977,"score_spread":0.331987582818098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391181","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44863823,0.00016096898,0.5487644,0.0017745962,0.00042702624,0.0001731046,0.000014220568,0.00004438342,0.0000030655376],"genre_scores_gemma":[0.9924889,0.000054326534,0.00674545,0.00035497663,0.00023587597,0.00003683022,0.000067674904,0.00000956545,0.0000064053447],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980433,0.00005887977,0.00031564748,0.00055497966,0.00075422064,0.00027295513],"domain_scores_gemma":[0.999133,0.0000872407,0.00009211331,0.00026448007,0.00019609554,0.00022709639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017468277,0.000104705265,0.000101664125,0.00048165448,0.00033587843,0.00062284386,0.00075362343,0.00003714848,0.0000020605103],"category_scores_gemma":[0.00050598645,0.00008722079,0.00001535649,0.00044293195,0.00003769061,0.0029825596,0.00037600665,0.0003103966,8.3051725e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000117404335,0.00006685158,0.043661647,0.000066046596,0.000066082954,0.000060049464,0.002816667,0.0021117327,0.018343158,0.049655993,0.000072183764,0.88296217],"study_design_scores_gemma":[0.0002198576,0.00007872527,0.025792468,0.00019999596,0.000007228973,0.000097666256,0.000053580257,0.97049624,0.00008530571,0.0024807404,0.000376419,0.00011177035],"about_ca_topic_score_codex":0.00045869782,"about_ca_topic_score_gemma":0.0017152678,"teacher_disagreement_score":0.9683845,"about_ca_system_score_codex":0.0002685814,"about_ca_system_score_gemma":0.000212224,"threshold_uncertainty_score":0.6006098},"labels":[],"label_agreement":null},{"id":"W4402391204","doi":"10.23889/ijpds.v9i5.2545","title":"Maternal immigrant status and survival among children with congenital heart disease","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; Newborn Screening Ontario","funders":"","keywords":"Immigration; Disease; Medicine; Heart disease; Pediatrics; Demography; Internal medicine; Geography; Sociology","score_opus":0.03440718145664302,"score_gpt":0.38150127854590893,"score_spread":0.3470940970892659,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391204","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98959714,0.00040951004,0.004158859,0.00066152314,0.003716112,0.00022769129,0.0011393433,0.000036993722,0.000052799904],"genre_scores_gemma":[0.99770576,0.000027752201,0.00089154416,0.0001269266,0.00055605307,0.0000109071625,0.0004818429,0.000012984593,0.00018622847],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982822,0.000028323928,0.00030422665,0.00042180583,0.00065965194,0.0003038134],"domain_scores_gemma":[0.9990369,0.00006719178,0.0000895145,0.00023562035,0.00020419923,0.00036654697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006854854,0.000108951164,0.0000893008,0.00028506387,0.0002964741,0.00073707575,0.0005329752,0.000024953804,0.00018661967],"category_scores_gemma":[0.00008790507,0.000084036896,0.000025717536,0.00017482438,0.00018801763,0.0017852442,0.00008421904,0.00014927788,0.000020496385],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022996888,0.000026403502,0.983128,0.000004620885,0.000066641405,0.000015129093,0.00034959702,0.000027523933,0.000010904546,0.009601495,0.00080679555,0.0057329168],"study_design_scores_gemma":[0.00050125096,0.00005503264,0.9928196,0.000040517207,0.00002719251,0.00022521673,0.00008955484,0.0032209277,0.0000023220127,0.0009754796,0.0019379234,0.00010495422],"about_ca_topic_score_codex":0.002705893,"about_ca_topic_score_gemma":0.0013268777,"teacher_disagreement_score":0.009691625,"about_ca_system_score_codex":0.00006571807,"about_ca_system_score_gemma":0.00018855184,"threshold_uncertainty_score":0.7107638},"labels":[],"label_agreement":null},{"id":"W4402391213","doi":"10.23889/ijpds.v9i5.2614","title":"Poverty and Intellectual Development in Childhood.","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Poverty; Economic growth; Economics","score_opus":0.05686276432627089,"score_gpt":0.41102805278898513,"score_spread":0.3541652884627142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391213","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94365627,0.0011446585,0.009907897,0.022060795,0.01713633,0.0006220616,0.00008317771,0.00013254404,0.005256279],"genre_scores_gemma":[0.98961735,0.00032237513,0.008217295,0.00051913335,0.0004652398,0.000004653745,0.00007467511,0.0000057918123,0.0007734968],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984499,0.000027120397,0.0002895223,0.000289048,0.0007422963,0.00020210267],"domain_scores_gemma":[0.9993611,0.00016806394,0.000050504383,0.000100398465,0.00018992207,0.0001300231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00228445,0.00006477935,0.000060148905,0.0004934246,0.00050123397,0.0010219967,0.0008550476,0.000028883656,0.00015190274],"category_scores_gemma":[0.0016933557,0.000058591246,0.000014551765,0.00041312122,0.000115153525,0.002137966,0.00017242406,0.00012862177,0.000021188169],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026372667,0.0001352672,0.065675445,0.000011138533,0.000053042266,0.000013384973,0.082130864,0.00006827778,0.00006555516,0.09618885,0.032233346,0.72339845],"study_design_scores_gemma":[0.0001775985,0.000009328336,0.2461135,0.000108278604,0.0000023674916,0.00003061389,0.0014299533,0.0012969318,0.000024017983,0.0032183074,0.7474505,0.00013863787],"about_ca_topic_score_codex":0.00027677746,"about_ca_topic_score_gemma":0.0007635628,"teacher_disagreement_score":0.7232598,"about_ca_system_score_codex":0.00035035828,"about_ca_system_score_gemma":0.0017592369,"threshold_uncertainty_score":0.98551375},"labels":[],"label_agreement":null},{"id":"W4402391230","doi":"10.23889/ijpds.v9i5.2890","title":"Providing data analytic services for national knowledge users in a federated system: learnings from two Canadian use cases","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University; Government of Newfoundland and Labrador; University of New Brunswick; Alberta Health; Manitoba Health; Canadian Institute for Health Information; Newfoundland and Labrador Centre for Applied Health Research; Alberta Health Services","funders":"","keywords":"Knowledge management; Computer science; Data science","score_opus":0.4809236346985375,"score_gpt":0.5410040609025777,"score_spread":0.060080426204040194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391230","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7268765,0.00066952035,0.13208228,0.01322738,0.025209596,0.002746198,0.09807085,0.0002420387,0.0008756292],"genre_scores_gemma":[0.9858396,0.000008626617,0.0051697777,0.00025807164,0.0005295594,0.000012742494,0.0075594364,0.000012603837,0.0006095769],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9953856,0.00012215406,0.00096235244,0.001078403,0.0021059206,0.00034558587],"domain_scores_gemma":[0.99476504,0.0025464757,0.0003353125,0.00071528944,0.0013959947,0.00024188327],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.011763232,0.00014917663,0.00019427392,0.0018383664,0.0007012323,0.009488595,0.005964127,0.000041019037,0.000080789396],"category_scores_gemma":[0.010558178,0.00012594374,0.00005254642,0.001218209,0.000090726964,0.0150584,0.0010420461,0.00016965663,0.000054496326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093173055,0.00034963002,0.1652997,0.0004317323,0.00086495944,0.00054297084,0.004277897,0.022208283,0.00091361644,0.2742108,0.24876885,0.2811998],"study_design_scores_gemma":[0.00034535493,0.00001671147,0.011215242,0.00024973185,0.000020309015,0.000048316237,0.0011067821,0.73665583,0.000007192781,0.002393683,0.24779417,0.00014664761],"about_ca_topic_score_codex":0.09150772,"about_ca_topic_score_gemma":0.5188786,"teacher_disagreement_score":0.71444756,"about_ca_system_score_codex":0.0008889749,"about_ca_system_score_gemma":0.001349568,"threshold_uncertainty_score":0.9994141},"labels":[],"label_agreement":null},{"id":"W4402391236","doi":"10.23889/ijpds.v9i5.2562","title":"Understanding the developmental well-being of children from refugee backgrounds in British Columbia, Canada: A population-level mixed methods approach","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; University of British Columbia","funders":"","keywords":"Refugee; Population; Psychology; Developmental psychology; Geography; Demography; Sociology; Archaeology","score_opus":0.13456248740990848,"score_gpt":0.40789371841613054,"score_spread":0.27333123100622203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391236","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8805355,0.00017476403,0.113128655,0.0003136023,0.004434235,0.0003026578,0.0007186431,0.000015013032,0.0003769512],"genre_scores_gemma":[0.9704914,0.00001252984,0.02713437,0.00013228977,0.00027609622,0.000012904951,0.0017385778,0.00001285298,0.00018896424],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99764717,0.00014027958,0.0007316226,0.00044342142,0.0007701312,0.00026736697],"domain_scores_gemma":[0.9989671,0.0003262216,0.00023724565,0.0002297467,0.00014311587,0.00009654197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024980276,0.000087459244,0.00014799951,0.00020450048,0.0004414898,0.0007509716,0.0012058215,0.00005359525,0.0002193256],"category_scores_gemma":[0.00028651897,0.00010009316,0.000038195423,0.00053070456,0.000086007545,0.0010543999,0.00013748607,0.0002414796,0.00000183202],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043360033,0.000091098336,0.9147763,0.000017713399,0.00018376794,0.0000138315645,0.0022415996,0.00035474135,0.000045283505,0.016814748,0.010137749,0.05527979],"study_design_scores_gemma":[0.00037803059,0.000010271444,0.97710127,0.00009439034,0.0000141862,0.00021931485,0.0015464972,0.012085773,0.000002813604,0.0076821954,0.0007508093,0.00011442785],"about_ca_topic_score_codex":0.837012,"about_ca_topic_score_gemma":0.9389574,"teacher_disagreement_score":0.10194544,"about_ca_system_score_codex":0.0010058612,"about_ca_system_score_gemma":0.0007287424,"threshold_uncertainty_score":0.72416365},"labels":[],"label_agreement":null},{"id":"W4402391243","doi":"10.23889/ijpds.v9i5.2487","title":"Ethnoracial disparities in childhood growth trajectories in Brazil: a longitudinal nationwide study of four million children","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Infection and Immunity","funders":"","keywords":"Demography; Environmental health; Geography; Medicine; Sociology","score_opus":0.05113928544764079,"score_gpt":0.38679275550140985,"score_spread":0.33565347005376905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391243","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928244,0.00009963381,0.00048241633,0.0022667714,0.0035381687,0.00042568878,0.00031842286,0.000027414611,0.000017107868],"genre_scores_gemma":[0.9986768,0.000021427319,0.0003877982,0.00006624912,0.00051197177,0.000011038665,0.00030558463,0.00001283237,0.0000062959502],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976637,0.0000610723,0.0006695796,0.00042070023,0.0009721728,0.00021279584],"domain_scores_gemma":[0.99916315,0.0001334546,0.00015924861,0.00018206719,0.00030602654,0.00005606433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011618085,0.00012593794,0.00017066399,0.0014802731,0.00017715387,0.0005989427,0.0011799489,0.00004160637,0.000014822304],"category_scores_gemma":[0.0006808654,0.00011754783,0.00004671655,0.00092518056,0.00009396363,0.0038533383,0.00017249883,0.0002654576,0.0000013706288],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018619826,0.00044800862,0.99417186,0.000014936831,0.000019218194,0.000011148579,0.0010743152,0.00035694824,0.000076272285,0.0008511726,0.00021719058,0.0025727167],"study_design_scores_gemma":[0.0013611993,0.00011945954,0.98769003,0.00022119217,0.000013209773,0.00009024403,0.00011788133,0.0046049077,0.0002512539,0.005360282,0.000043456177,0.0001268624],"about_ca_topic_score_codex":0.0028931943,"about_ca_topic_score_gemma":0.004413202,"teacher_disagreement_score":0.006481822,"about_ca_system_score_codex":0.00019363298,"about_ca_system_score_gemma":0.00006794186,"threshold_uncertainty_score":0.5775618},"labels":[],"label_agreement":null},{"id":"W4402391272","doi":"10.23889/ijpds.v9i5.2864","title":"Exploring Text Classification Systems for Automatically Coding Historical Occupations and Causes of Death","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Guelph","funders":"Economic and Social Research Council","keywords":"Coding (social sciences); Computer science; Natural language processing; Information retrieval; Data science; Sociology; Social science","score_opus":0.5370092133463087,"score_gpt":0.5151466273038554,"score_spread":0.02186258604245328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391272","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08246567,0.00040252955,0.9080558,0.0028873784,0.005378975,0.00032346742,0.00018347635,0.000059474976,0.00024324324],"genre_scores_gemma":[0.9729191,0.00024118238,0.02591188,0.0000130250655,0.0006058129,0.000027082013,0.00008749712,0.000005845141,0.00018858466],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99829733,0.000062192994,0.0004495347,0.00026233526,0.0007873492,0.0001412287],"domain_scores_gemma":[0.9978114,0.0009616854,0.00019212316,0.00012007621,0.0008163378,0.00009838619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031232971,0.00006393321,0.00011685822,0.00045694757,0.00064217695,0.0006253299,0.0006227663,0.000025093748,0.000008207904],"category_scores_gemma":[0.00261095,0.000057768644,0.000052898184,0.00039045472,0.00011045093,0.0025847366,0.00007810712,0.00006415601,0.000001007108],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021254496,0.00003635129,0.0076377033,0.000039838313,0.000062533145,0.0000010480536,0.0012008903,0.0011598277,0.0007074776,0.93427426,0.0006913895,0.054167416],"study_design_scores_gemma":[0.00017774604,0.00003501042,0.057605393,0.00017723482,0.00006889058,0.000016963084,0.00071173906,0.86496586,0.000020053027,0.016198618,0.059881542,0.00014093745],"about_ca_topic_score_codex":0.0006655654,"about_ca_topic_score_gemma":0.000091882845,"teacher_disagreement_score":0.9180757,"about_ca_system_score_codex":0.00047546782,"about_ca_system_score_gemma":0.00033432047,"threshold_uncertainty_score":0.6030071},"labels":[],"label_agreement":null},{"id":"W4402391584","doi":"10.23889/ijpds.v9i5.2671","title":"Practical approaches for engaging the public in a population-level data analysis project.","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Community Health and Development","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Sunnybrook Health Science Centre; Hospital for Sick Children","funders":"","keywords":"Population; Data science; Computer science; Sociology","score_opus":0.7767127745946109,"score_gpt":0.6304099644816519,"score_spread":0.14630281011295898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391584","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054337773,0.0003736302,0.7220569,0.20093244,0.012042354,0.0045656892,0.005075298,0.00014223246,0.00047362494],"genre_scores_gemma":[0.9354838,0.000058523674,0.055065732,0.0008735968,0.0006798982,0.00015115974,0.007465656,0.000013905675,0.0002076936],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969172,0.00030847255,0.00088264106,0.0005110418,0.0009225584,0.000458103],"domain_scores_gemma":[0.9956416,0.0024982237,0.00030363063,0.0009827642,0.00044650066,0.00012727118],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.013976385,0.00011341504,0.00016897493,0.0011582139,0.0020133136,0.0005594166,0.0029705178,0.00006213348,0.000045281493],"category_scores_gemma":[0.0088838395,0.00008002159,0.000050755014,0.0015516165,0.00007361668,0.0039893333,0.0013010793,0.0007434353,0.000008171995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028724433,0.00027576974,0.4594846,0.00026734857,0.00055892183,0.000012631122,0.0048100716,0.0005509112,0.00000939314,0.31356782,0.058225654,0.16194965],"study_design_scores_gemma":[0.00036146157,0.000012370966,0.18081889,0.00010806554,0.00006249092,0.000023676734,0.0017220186,0.6969006,1.8497542e-7,0.005192974,0.11468122,0.000116037765],"about_ca_topic_score_codex":0.0013796861,"about_ca_topic_score_gemma":0.007348343,"teacher_disagreement_score":0.8811461,"about_ca_system_score_codex":0.00054887624,"about_ca_system_score_gemma":0.0023798733,"threshold_uncertainty_score":0.99946475},"labels":[],"label_agreement":null},{"id":"W4402391614","doi":"10.23889/ijpds.v9i5.2702","title":"Minor Ailments and Pharmacist Management in Ontario, Canada: Attachment and Primary Care","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"St. Michael's Hospital; Queen's University; University of Toronto","funders":"","keywords":"Pharmacist; Primary care; Minor (academic); Medicine; Family medicine; Nursing; Pharmacy; Political science","score_opus":0.18057706333626752,"score_gpt":0.4712401610661345,"score_spread":0.290663097729867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99222404,0.000807128,0.00019615331,0.0023833953,0.0025908505,0.00036379544,0.00012498558,0.000007449717,0.0013022115],"genre_scores_gemma":[0.9965544,0.00017281187,0.0016732785,0.0007719426,0.000065179825,0.0000041486473,0.00030011838,0.000003721272,0.00045441347],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99888587,0.000007496761,0.00020379547,0.00022610657,0.00056050764,0.000116210096],"domain_scores_gemma":[0.999644,0.00004281342,0.000046099252,0.00008417951,0.000066922905,0.00011599704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000318729,0.00006124066,0.000070822985,0.00015420065,0.00008859227,0.00018749421,0.0002027854,0.00000962939,0.000036414003],"category_scores_gemma":[0.000027573478,0.000050112463,0.000010390235,0.000073943505,0.000037798334,0.00093571865,0.00019640147,0.0001351582,7.567981e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018430059,0.00003477854,0.93968725,0.00012891131,0.00007500617,0.00018235452,0.00020807731,0.000018059403,0.00012184198,0.0006434382,0.0013662264,0.057349723],"study_design_scores_gemma":[0.0011559055,0.000033880744,0.79873496,0.00018274199,0.00006233877,0.0002305303,0.00010852996,0.01563652,0.000021461083,0.00009407572,0.18365902,0.00008004405],"about_ca_topic_score_codex":0.116244294,"about_ca_topic_score_gemma":0.20131963,"teacher_disagreement_score":0.18229279,"about_ca_system_score_codex":0.0008227825,"about_ca_system_score_gemma":0.0003171523,"threshold_uncertainty_score":0.8896407},"labels":[],"label_agreement":null},{"id":"W4402391702","doi":"10.23889/ijpds.v9i5.2719","title":"Quality of care for community-dwelling older adults living with dementia in BC: an interrupted time-series analysis to examine the effect of the COVID-19 pandemic","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Dementia; Gerontology; Interrupted time series; Interrupted Time Series Analysis; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medicine; Psychiatry; Virology; Disease; Psychological intervention","score_opus":0.11319352273929571,"score_gpt":0.49869727265468106,"score_spread":0.38550374991538533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402391702","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97601426,0.00011415579,0.02137285,0.0006496231,0.00084681174,0.00059632317,0.00038358066,0.000011685878,0.000010696878],"genre_scores_gemma":[0.9988252,0.0000070740034,0.000702654,0.000067549176,0.00008499801,0.000023402072,0.00024701367,0.0000061922537,0.00003594127],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99804115,0.00059532025,0.00055316096,0.00017830047,0.00048214485,0.00014994963],"domain_scores_gemma":[0.9966199,0.0021304637,0.00033551134,0.00040015782,0.00045130486,0.00006269421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058415425,0.00007764997,0.00019014881,0.0003889633,0.00068790774,0.00006339873,0.001280964,0.000033306453,0.000032482523],"category_scores_gemma":[0.0022635132,0.00004276471,0.000069932095,0.0008214613,0.00009973108,0.00062448316,0.0002499477,0.000252586,4.8198524e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051459804,0.00002346459,0.9674138,0.00027574456,0.00016061963,1.9336915e-7,0.02251407,0.003813223,0.00036670198,0.0001237256,0.00019317791,0.004600717],"study_design_scores_gemma":[0.0006645031,0.0003544928,0.9691974,0.0009824102,0.00024033131,0.0000059018307,0.013058512,0.014598104,0.00006584418,0.00011029853,0.00062350853,0.000098685734],"about_ca_topic_score_codex":0.0044260737,"about_ca_topic_score_gemma":0.020359905,"teacher_disagreement_score":0.022810902,"about_ca_system_score_codex":0.00022657697,"about_ca_system_score_gemma":0.0002309447,"threshold_uncertainty_score":0.997516},"labels":[],"label_agreement":null},{"id":"W4402404927","doi":"10.23889/ijpds.v9i5.2634","title":"Administrative health data validity: Changes over 19 years","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Libin Cardiovascular Institute of Alberta; Alberta Health Services; University of Calgary","funders":"","keywords":"Computer science; Data science; Psychology","score_opus":0.8354082115284943,"score_gpt":0.6199838554586272,"score_spread":0.2154243560698671,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402404927","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10176349,0.011180908,0.20184055,0.5454944,0.053620096,0.0023798854,0.0817946,0.00031097277,0.0016151256],"genre_scores_gemma":[0.9392095,0.0014431612,0.026484124,0.01877447,0.0052504633,0.000034859044,0.007568893,0.000053790878,0.0011807022],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99646133,0.00010106469,0.0018833008,0.0008226861,0.0004120051,0.00031958235],"domain_scores_gemma":[0.9969243,0.00056493207,0.0012233417,0.00089591474,0.00013009703,0.00026141806],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.027179593,0.0001191729,0.0003226094,0.00064586947,0.00036078575,0.0011394792,0.0028618998,0.00004689426,0.0002891386],"category_scores_gemma":[0.005934411,0.0001392191,0.00004292111,0.00030282346,0.00011202,0.0047477013,0.0005027391,0.00018614567,0.00023662359],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033662607,0.00010183377,0.022272214,0.0001559321,0.00015493076,0.00001258095,0.0014421064,0.00018832412,0.000009885221,0.36346477,0.5974981,0.01466567],"study_design_scores_gemma":[0.00033428095,0.000085158616,0.04913169,0.00016184465,0.0000053050294,0.00008394676,0.00024729298,0.1124525,0.000001355002,0.02211583,0.8151524,0.00022836323],"about_ca_topic_score_codex":0.0009783759,"about_ca_topic_score_gemma":0.0005949293,"teacher_disagreement_score":0.83744603,"about_ca_system_score_codex":0.0008246751,"about_ca_system_score_gemma":0.00090065226,"threshold_uncertainty_score":0.9998974},"labels":[],"label_agreement":null},{"id":"W4402404930","doi":"10.23889/ijpds.v9i5.2627","title":"The role of emergency department crowding on the implementation of efficiency strategies to improve care for adult patients presenting with chest pain.","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Alberta","funders":"","keywords":"Emergency department; Crowding; Chest pain; Medicine; Medical emergency; Emergency medicine; Operations management; Psychology; Internal medicine; Nursing; Engineering; Cognitive psychology","score_opus":0.18309590073585,"score_gpt":0.47741096162099056,"score_spread":0.2943150608851406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402404930","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94610953,0.0003146668,0.038083166,0.008239796,0.0026421836,0.0016158659,0.0028286404,0.000010441562,0.00015572576],"genre_scores_gemma":[0.9978332,0.000022750963,0.001543754,0.0001653105,0.00018626821,0.00007924856,0.00014790181,0.000008584389,0.000012988309],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99768543,0.000050988525,0.0015075915,0.00028229904,0.0002944073,0.00017928627],"domain_scores_gemma":[0.99712837,0.00064347254,0.0011202372,0.00026065533,0.00080069224,0.00004657587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008236797,0.00007686742,0.00014218986,0.00019808488,0.0004528856,0.00028499216,0.00087730295,0.000016538128,0.000016919106],"category_scores_gemma":[0.0029167891,0.000055141678,0.00005016872,0.00018243794,0.000043357628,0.0010625466,0.00008141883,0.000046279132,0.000003721038],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009535477,0.00009557483,0.1971787,0.00026989487,0.00015852132,1.2752696e-7,0.0070387744,0.0040664906,0.00016928217,0.7714219,0.002933362,0.016571986],"study_design_scores_gemma":[0.001873047,0.0017416851,0.4310338,0.000574122,0.000054481025,0.0000040856794,0.07984244,0.32904685,0.0016333212,0.08094512,0.07254925,0.0007018115],"about_ca_topic_score_codex":0.00030806114,"about_ca_topic_score_gemma":0.00031968165,"teacher_disagreement_score":0.69047683,"about_ca_system_score_codex":0.00024282897,"about_ca_system_score_gemma":0.00018940054,"threshold_uncertainty_score":0.34918797},"labels":[],"label_agreement":null},{"id":"W4402404951","doi":"10.23889/ijpds.v9i5.2629","title":"Navigating the barriers to multi-regional research administrative data access: Forward thinking solutions","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; University of New Brunswick","funders":"","keywords":"Computer science; Data access; Data science; Business; Knowledge management; Process management; Database","score_opus":0.791276926938249,"score_gpt":0.6602605995632315,"score_spread":0.13101632737501756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402404951","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08334486,0.00048141618,0.8181153,0.085066795,0.00940714,0.0007806881,0.0024841465,0.000101160804,0.00021852003],"genre_scores_gemma":[0.9770352,0.00006894098,0.020720055,0.0007085681,0.00072711636,0.00002173666,0.0005647421,0.000013758106,0.00013983002],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9911892,0.0002472717,0.0009279677,0.0010884191,0.0060611605,0.00048602838],"domain_scores_gemma":[0.9923525,0.002641752,0.0002731484,0.0015043461,0.002832552,0.0003956924],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03659008,0.00013542273,0.00013326407,0.0006282834,0.0035683352,0.010207129,0.015781157,0.000049326452,0.000108666274],"category_scores_gemma":[0.027719624,0.000087366236,0.00007695152,0.0025176904,0.0004428074,0.009595108,0.0032049466,0.00074970984,0.000059520746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023819538,0.00014450973,0.016827041,0.00001476127,0.00026147426,0.000048829465,0.012158389,0.042207584,0.0009336011,0.16894133,0.15260525,0.605619],"study_design_scores_gemma":[0.00014750593,0.00003612851,0.0058398824,0.00019700898,0.000013140093,0.00009744684,0.0042890636,0.8805877,0.000008334179,0.06121036,0.047441706,0.00013173067],"about_ca_topic_score_codex":0.00041487362,"about_ca_topic_score_gemma":0.0008318627,"teacher_disagreement_score":0.8936904,"about_ca_system_score_codex":0.00018213726,"about_ca_system_score_gemma":0.0012065242,"threshold_uncertainty_score":0.9977289},"labels":[],"label_agreement":null},{"id":"W4402404954","doi":"10.23889/ijpds.v9i5.2618","title":"Integrating Gender Identity and Sexual Orientation in Population-Based Administrative Data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Gender Politics and Representation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Sexual orientation; Identity (music); Orientation (vector space); Sexual identity; Gender identity; Population; Psychology; Data science; Computer science; Social psychology; Sociology; Gender studies; Human sexuality; Mathematics; Demography","score_opus":0.2925273921813333,"score_gpt":0.5328421313644996,"score_spread":0.24031473918316637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402404954","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8826252,0.00022798347,0.10022208,0.005187705,0.008690314,0.00066054414,0.0012358808,0.00007929184,0.0010709557],"genre_scores_gemma":[0.99160975,0.00002496601,0.0058584986,0.000086335356,0.00058451924,0.000005059083,0.0017363243,0.000007167104,0.00008738227],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9976605,0.000093824645,0.00040489604,0.00052311266,0.0010931337,0.00022449571],"domain_scores_gemma":[0.9988546,0.0002523366,0.00014874285,0.00029827017,0.00032700488,0.00011904604],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0032967096,0.000086333515,0.000082272454,0.00044500217,0.00061006343,0.0017925017,0.0013401819,0.000045588316,0.000036422723],"category_scores_gemma":[0.0019050424,0.000081041144,0.000016201348,0.0004734185,0.0001667644,0.0074488386,0.0002449324,0.0001591334,0.000002830645],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003676625,0.000082098144,0.4691954,0.00003310746,0.000043417498,0.000022565788,0.006436603,0.000796353,0.00032786815,0.4892861,0.00081681454,0.032922916],"study_design_scores_gemma":[0.00045376454,0.000033588625,0.5638768,0.00009480492,0.00002902206,0.000025872332,0.0078075556,0.37465817,0.000018614031,0.048233945,0.0045237686,0.00024409548],"about_ca_topic_score_codex":0.007027453,"about_ca_topic_score_gemma":0.009699149,"teacher_disagreement_score":0.44105214,"about_ca_system_score_codex":0.00029654457,"about_ca_system_score_gemma":0.00069299055,"threshold_uncertainty_score":0.99958485},"labels":[],"label_agreement":null},{"id":"W4402404959","doi":"10.23889/ijpds.v9i5.2628","title":"Enhancing population-level research among people who inject drugs: a validation and retrospective cohort study using health administrative data in Ontario, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"HIV, Drug Use, Sexual Risk","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo; Toronto Public Health; Bruyère; University of Toronto; University Health Network; Jewish General Hospital; Public Health Ontario; BC Centre for Disease Control","funders":"","keywords":"Medicine; Retrospective cohort study; Environmental health; Cohort; Cohort study; Population; Health data; Family medicine; Health care; Political science; Internal medicine","score_opus":0.2600636427680832,"score_gpt":0.5133669542040653,"score_spread":0.2533033114359821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402404959","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99433124,0.00004648042,0.001567265,0.00068936433,0.0012600697,0.0012540792,0.0007697172,0.000017328142,0.00006447506],"genre_scores_gemma":[0.9948894,0.000016222555,0.002372297,0.00004737708,0.00027004385,0.000014313355,0.002167032,0.000020289783,0.00020302027],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99479103,0.00018238334,0.00082830375,0.00096411235,0.002805644,0.0004285164],"domain_scores_gemma":[0.9975782,0.0003139522,0.00027421367,0.00070615165,0.0008652933,0.00026221183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009003993,0.00016360554,0.0003369702,0.000897243,0.00060471735,0.0007122389,0.0010895962,0.000042873973,0.00004217677],"category_scores_gemma":[0.002786597,0.00015454882,0.0000178782,0.0010209216,0.0001094406,0.0037289432,0.0006826575,0.00070672436,8.681407e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00006577342,0.00007662328,0.99052835,0.000018483277,0.000057847894,0.000024698245,0.00728558,0.0001298479,0.000059050693,0.00020296719,0.00035720028,0.00119361],"study_design_scores_gemma":[0.00046810252,0.00016569499,0.93178636,0.00043776794,0.000023240873,0.000112302696,0.010757206,0.055749707,0.000020835676,0.00027741224,0.0000741741,0.00012718816],"about_ca_topic_score_codex":0.9572358,"about_ca_topic_score_gemma":0.9925579,"teacher_disagreement_score":0.05874195,"about_ca_system_score_codex":0.0059606377,"about_ca_system_score_gemma":0.0068754987,"threshold_uncertainty_score":0.9987546},"labels":[],"label_agreement":null},{"id":"W4402404963","doi":"10.23889/ijpds.v9i5.2624","title":"From Probabilistic to Fuzzy Matching Record Linkage: A promising Transition","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Probabilistic logic; Matching (statistics); Transition (genetics); Linkage (software); Computer science; Record linkage; Fuzzy logic; Data mining; Artificial intelligence; Mathematics; Biology; Genetics; Statistics; Sociology","score_opus":0.24547470867080023,"score_gpt":0.5016516879164926,"score_spread":0.2561769792456924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402404963","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19466418,0.00003790429,0.77294815,0.018404268,0.011138708,0.0004731304,0.0019156949,0.00007536018,0.0003425917],"genre_scores_gemma":[0.940707,0.000009808396,0.05571961,0.0008955071,0.0015107207,0.000013972758,0.0007179431,0.000012356561,0.00041302617],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99531275,0.000090420486,0.0008622272,0.0008333096,0.0026665777,0.00023470377],"domain_scores_gemma":[0.9977128,0.0006455926,0.00019582434,0.0006659527,0.0005966003,0.00018325522],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.008973889,0.000115856776,0.00014322823,0.00078029756,0.00046332073,0.005798174,0.0038793266,0.00003221971,0.00017217478],"category_scores_gemma":[0.0045906766,0.000091662325,0.00007003001,0.0008644378,0.00008288154,0.006713409,0.0006014244,0.00017572743,0.000190028],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015736445,0.00009672051,0.00022385089,0.00002005972,0.00006496019,0.000047754336,0.0037561767,0.008350462,0.002697369,0.04998855,0.0342724,0.90032434],"study_design_scores_gemma":[0.00027359207,0.00006323039,0.0057203015,0.0003412433,0.000030230958,0.000047037127,0.000943079,0.14849105,0.000053570813,0.691453,0.15233374,0.0002499561],"about_ca_topic_score_codex":0.0005538721,"about_ca_topic_score_gemma":0.00023000468,"teacher_disagreement_score":0.90007436,"about_ca_system_score_codex":0.00022475798,"about_ca_system_score_gemma":0.00018322188,"threshold_uncertainty_score":0.9952339},"labels":[],"label_agreement":null},{"id":"W4402404964","doi":"10.23889/ijpds.v9i5.2619","title":"Healthcare costs at the end-of-life among immigrant and non-immigrant groups in Manitoba, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Immigration; Health care; Demographic economics; Gerontology; Psychology; Medicine; Political science; Economics; Economic growth","score_opus":0.05466686035648381,"score_gpt":0.3763597626944621,"score_spread":0.32169290233797826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402404964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98582035,0.0012009003,0.0005529922,0.006074793,0.005176186,0.00031155624,0.0007959168,0.00000736044,0.000059933856],"genre_scores_gemma":[0.9985959,0.00010243688,0.00011010219,0.0004658813,0.00028923104,0.000016366364,0.00031739162,0.000008491986,0.00009420891],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980213,0.000056929202,0.0005805813,0.0003527769,0.00071995193,0.00026842745],"domain_scores_gemma":[0.9988909,0.0002309787,0.00019885274,0.00029320424,0.00021008751,0.00017598752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014670788,0.0000998419,0.00012281243,0.0002619178,0.0003104354,0.00015450385,0.00086578575,0.000037748818,0.00009146642],"category_scores_gemma":[0.0002017699,0.00007283957,0.00002751606,0.00031154326,0.00017093943,0.000695729,0.0001326245,0.00020816784,0.0000043578075],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002589919,0.000051480816,0.9057344,0.00006766333,0.000060488594,0.000058946756,0.0041595255,0.00012069533,0.00010401324,0.021354487,0.014180788,0.053848494],"study_design_scores_gemma":[0.00040295167,0.000034319306,0.98295283,0.00012276141,0.0000069297407,0.00012807039,0.0015458436,0.008357064,0.000011724822,0.0004951898,0.0058549317,0.0000873587],"about_ca_topic_score_codex":0.8236453,"about_ca_topic_score_gemma":0.9823475,"teacher_disagreement_score":0.15870221,"about_ca_system_score_codex":0.00047991142,"about_ca_system_score_gemma":0.00068077474,"threshold_uncertainty_score":0.29703113},"labels":[],"label_agreement":null},{"id":"W4402404990","doi":"10.23889/ijpds.v9i5.2566","title":"Healthcare use among people using methamphetamine in Winnipeg, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Substance Abuse Treatment and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; George & Fay Yee Centre for Healthcare Innovation; Manitoba Health","funders":"","keywords":"Methamphetamine; Health care; Business; Internet privacy; Psychology; Computer science; Political science; Psychiatry; Law","score_opus":0.11797695705754378,"score_gpt":0.4161484603109085,"score_spread":0.2981715032533647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402404990","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9931183,0.0002810478,0.0011956531,0.0021985916,0.0029263918,0.00017605124,0.00007749353,0.000016565284,0.000009897161],"genre_scores_gemma":[0.9950144,0.00004807696,0.003843214,0.00023949055,0.00026266288,0.0000025345707,0.00034622895,0.00000970037,0.000233654],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998415,0.00001353991,0.0003174121,0.00027230548,0.0007857459,0.00019600139],"domain_scores_gemma":[0.9992069,0.00012029278,0.00007921928,0.00021717168,0.0002598738,0.00011655853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051716564,0.00008615754,0.00013180348,0.0003779102,0.000118432916,0.00024358903,0.00040090582,0.000022277029,0.00003243593],"category_scores_gemma":[0.0004408815,0.00006908802,0.000033396816,0.0004837784,0.00004021059,0.0023988723,0.00007283706,0.000127135,0.0000010684043],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039121765,0.000015702859,0.99403596,0.000008243635,0.000028742645,0.00011363516,0.00015571232,0.00029499398,0.00018798094,0.0004974839,0.000458204,0.004164244],"study_design_scores_gemma":[0.0005889762,0.000018644145,0.8968951,0.0002827178,0.00002697977,0.00026276152,0.00017476501,0.09961491,0.0000833468,0.00017022062,0.0017953997,0.00008617277],"about_ca_topic_score_codex":0.20045719,"about_ca_topic_score_gemma":0.6689905,"teacher_disagreement_score":0.4685333,"about_ca_system_score_codex":0.00095085835,"about_ca_system_score_gemma":0.0010116177,"threshold_uncertainty_score":0.804867},"labels":[],"label_agreement":null},{"id":"W4402405004","doi":"10.23889/ijpds.v9i5.2495","title":"Linking trial data to ICES: incorporating a prompt in a research ethics protocol submission platform in Southwestern Ontario","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"","keywords":"Protocol (science); Research ethics; Computer science; Data science; Medicine; Engineering ethics; Engineering; Alternative medicine","score_opus":0.9259707287505733,"score_gpt":0.7365309684394505,"score_spread":0.18943976031112275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405004","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8927686,0.000022491422,0.004831926,0.028340802,0.0042196894,0.06866222,0.00036393895,0.00007224605,0.00071805314],"genre_scores_gemma":[0.97377586,0.000008832817,0.019266,0.0003448678,0.0014868411,0.0034026215,0.00081797014,0.000032298798,0.0008646793],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9914145,0.00016016744,0.0012974031,0.0010386806,0.0056014694,0.00048779373],"domain_scores_gemma":[0.9904681,0.0057687177,0.00022750383,0.0012777429,0.0018877685,0.00037017552],"candidate_categories":["metaresearch","scholarly_communication","research_integrity"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.07298691,0.000126056,0.00021863963,0.0018039378,0.00033709055,0.001393319,0.00414284,0.00026241696,0.00005444561],"category_scores_gemma":[0.061073035,0.000102064194,0.00003688337,0.0014455487,0.00024022916,0.0032827605,0.0030717808,0.005800593,0.000021125987],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.063239925,0.0019163346,0.72558,0.0016739521,0.00011445831,0.0015511325,0.018400453,0.0013831586,0.0068288394,0.052215014,0.0012276465,0.12586911],"study_design_scores_gemma":[0.043494586,0.0031270152,0.1548677,0.035149723,0.000029093415,0.0004778578,0.0014181025,0.49277198,0.000222777,0.21497604,0.05268857,0.0007765578],"about_ca_topic_score_codex":0.010217907,"about_ca_topic_score_gemma":0.19934173,"teacher_disagreement_score":0.57071227,"about_ca_system_score_codex":0.0016445767,"about_ca_system_score_gemma":0.009088243,"threshold_uncertainty_score":0.9996433},"labels":[],"label_agreement":null},{"id":"W4402405015","doi":"10.23889/ijpds.v9i5.2553","title":"Free Text Analysis: Identification of adverse drug events in clinical notes","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Identification (biology); Drug; Computer science; Drug reaction; Adverse effect; Natural language processing; Medicine; Pharmacology; Biology","score_opus":0.06472439430834917,"score_gpt":0.44615202051066194,"score_spread":0.38142762620231274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405015","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96124506,0.00025423875,0.035330147,0.00080827164,0.0019383805,0.00006769846,0.0003365325,0.000006701373,0.000012986222],"genre_scores_gemma":[0.9968401,0.00007340084,0.00223097,0.000028688017,0.00023483604,0.0000024417084,0.0004975722,0.000003309365,0.00008867301],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986003,0.000035795263,0.000571215,0.00030264613,0.00039152213,0.00009852327],"domain_scores_gemma":[0.99917257,0.00007465276,0.00017895646,0.00033694305,0.00019090992,0.000045941164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024006073,0.000053015585,0.00009189515,0.00032915358,0.00004882407,0.000032120344,0.0012872467,0.000047442325,0.0000083332325],"category_scores_gemma":[0.002670378,0.000044571312,0.00008852075,0.00037926616,0.00013975371,0.00005637826,0.00026982534,0.00008298476,0.000001865095],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017088871,0.00019841916,0.845258,0.000022398684,0.00048679442,0.0000069314024,0.00012133408,0.0017420717,0.032063592,0.0013487635,0.0025233764,0.11605741],"study_design_scores_gemma":[0.00038906597,0.00004765586,0.9528227,0.00005403252,0.00007105861,0.000014414659,0.00006672146,0.03725462,0.0020207674,0.0017812058,0.0053797974,0.00009798907],"about_ca_topic_score_codex":0.000056908833,"about_ca_topic_score_gemma":0.00021558689,"teacher_disagreement_score":0.11595942,"about_ca_system_score_codex":0.000023327148,"about_ca_system_score_gemma":0.000116664676,"threshold_uncertainty_score":0.31968847},"labels":[],"label_agreement":null},{"id":"W4402405018","doi":"10.23889/ijpds.v9i5.2503","title":"How DASH enables external data linkage to support multi-regional research","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Sherbrooke; Canadian Institute for Health Information","funders":"","keywords":"Dash; Linkage (software); Computer science; Data science; Data mining; Biology; Genetics","score_opus":0.6136190081818458,"score_gpt":0.5738041924657937,"score_spread":0.039814815716052054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405018","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019157013,0.00019303792,0.95388097,0.037962843,0.004439754,0.0004461817,0.0009069599,0.00009750522,0.00015707282],"genre_scores_gemma":[0.3668198,0.0009322286,0.6155233,0.0009388808,0.002866322,0.000045806915,0.0027043293,0.000040822564,0.0101285605],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9918736,0.00018343976,0.00049047184,0.0016693005,0.005039147,0.0007440379],"domain_scores_gemma":[0.9940874,0.0006953055,0.00017097553,0.0032177828,0.0013755481,0.000452963],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.017541641,0.00017210217,0.00013679895,0.001937861,0.0008634595,0.04226811,0.03803387,0.00004535107,0.00003389849],"category_scores_gemma":[0.006594746,0.00014898363,0.000045597764,0.001683957,0.0002453764,0.1450847,0.015546015,0.00060036767,0.000103152655],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007858399,0.0002717751,0.0026206598,0.00006659539,0.00015247172,0.0005685252,0.00031163788,0.00048662015,0.005868618,0.4771923,0.17404379,0.33833843],"study_design_scores_gemma":[0.00025001695,0.000095548494,0.0053474875,0.00013784516,0.00000634965,0.00025449783,0.000070649745,0.36091268,0.000090554524,0.0027992397,0.6298487,0.00018643119],"about_ca_topic_score_codex":0.00021186053,"about_ca_topic_score_gemma":0.0001591989,"teacher_disagreement_score":0.47439307,"about_ca_system_score_codex":0.00033346785,"about_ca_system_score_gemma":0.0008815527,"threshold_uncertainty_score":0.9924161},"labels":[],"label_agreement":null},{"id":"W4402405099","doi":"10.23889/ijpds.v9i5.2490","title":"Healthcare contact days for people with stage IV non-small cell lung cancer (NSCLC) in Ontario: A population-based study","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University","funders":"","keywords":"Stage (stratigraphy); Lung cancer; Medicine; Cancer; Health care; Population; Oncology; Internal medicine; Gerontology; Environmental health; Biology; Political science","score_opus":0.10139296415002347,"score_gpt":0.4247554933755445,"score_spread":0.32336252922552106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405099","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9749957,0.0001777216,0.01953709,0.001675445,0.001565693,0.0014678523,0.0005138168,0.000026261898,0.00004045613],"genre_scores_gemma":[0.99356544,0.0000063802586,0.004598414,0.00040810305,0.00025919895,0.000108708504,0.00076052954,0.00001885999,0.00027434464],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975517,0.00002041625,0.00051606866,0.0005515992,0.0010334946,0.00032673278],"domain_scores_gemma":[0.9985365,0.00012338099,0.00020699376,0.00031048807,0.0006447373,0.00017784623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012152905,0.00015906924,0.00024131623,0.0004768897,0.0002629978,0.00042576063,0.00072007236,0.000041426207,0.000066673514],"category_scores_gemma":[0.00014869538,0.00012868305,0.00006105537,0.00043180506,0.00001880449,0.0014049325,0.00008347354,0.00029286102,0.0000013166143],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005989574,0.00008731724,0.9930787,0.00007064112,0.000032382177,0.000036946807,0.0005679795,0.0038237462,0.0001162686,0.00019623825,0.00023807578,0.0011527612],"study_design_scores_gemma":[0.0019634727,0.00040440122,0.8476819,0.0007577347,0.000058607642,0.000025536536,0.00044140813,0.14771105,0.000021722097,0.000048708138,0.00074498024,0.00014051469],"about_ca_topic_score_codex":0.20176046,"about_ca_topic_score_gemma":0.58882505,"teacher_disagreement_score":0.3870646,"about_ca_system_score_codex":0.0017206607,"about_ca_system_score_gemma":0.002347556,"threshold_uncertainty_score":0.8035551},"labels":[],"label_agreement":null},{"id":"W4402405108","doi":"10.23889/ijpds.v9i5.2616","title":"Wastewater-based surveillance for SARS-CoV-2 in Alberta","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Wastewater; Coronavirus disease 2019 (COVID-19); Environmental science; 2019-20 coronavirus outbreak; Waste management; Virology; Engineering; Environmental engineering; Medicine; Outbreak; Infectious disease (medical specialty)","score_opus":0.11829145714267106,"score_gpt":0.42819070537077875,"score_spread":0.30989924822810766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405108","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9690735,0.000059937465,0.021513654,0.0038727322,0.00464486,0.00038461192,0.00017517243,0.000053917804,0.00022161946],"genre_scores_gemma":[0.9910637,0.0000025201173,0.0073279752,0.00078887213,0.00048255987,0.000015503492,0.00021428765,0.000015894824,0.00008869293],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839514,0.000015719885,0.00042239702,0.0003888348,0.00055104424,0.00022683914],"domain_scores_gemma":[0.99890846,0.00033327652,0.00011048034,0.00025018677,0.0003565891,0.00004098488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013649554,0.00010242796,0.00013212205,0.0005999214,0.00014186803,0.00038510788,0.0006001033,0.000038346978,0.000007746603],"category_scores_gemma":[0.0021850802,0.00008729815,0.00006695293,0.00041998673,0.00006775547,0.0010517974,0.0000774064,0.000149484,0.000011713294],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060607516,0.00016866905,0.061187267,0.00012436752,0.00007203926,0.0000673416,0.00015574954,0.00042976177,0.8834236,0.004025862,0.0037753982,0.045963842],"study_design_scores_gemma":[0.0017585559,0.00015139903,0.012386685,0.000444051,0.00001743335,0.0005398703,0.00002482179,0.7627868,0.14785685,0.0016786044,0.07215536,0.00019956316],"about_ca_topic_score_codex":0.00049455307,"about_ca_topic_score_gemma":0.00077076844,"teacher_disagreement_score":0.76235706,"about_ca_system_score_codex":0.00023636976,"about_ca_system_score_gemma":0.0002801994,"threshold_uncertainty_score":0.37136042},"labels":[],"label_agreement":null},{"id":"W4402405308","doi":"10.23889/ijpds.v9i5.2653","title":"Identifying homelessness using health administrative data in Ontario, Canada: how coding policies impact case validity","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Coding (social sciences); Business; Environmental health; Public economics; Sociology; Medicine; Economics","score_opus":0.5464313889638716,"score_gpt":0.5937311837771718,"score_spread":0.04729979481330027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98021847,0.00014524047,0.0082080625,0.0015224762,0.006584202,0.00034214972,0.0029306037,0.00002157539,0.000027237116],"genre_scores_gemma":[0.997091,0.00004404779,0.0010096629,0.0000644347,0.00063274667,0.000005808244,0.0010737553,0.000014479378,0.00006404076],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99717444,0.00020377131,0.0006511191,0.00049068406,0.00096632686,0.00051363296],"domain_scores_gemma":[0.9980716,0.00040311244,0.00040556482,0.0004698783,0.00042712124,0.00022270894],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0039677457,0.00014701602,0.00031403961,0.0004016114,0.0016477765,0.0007342398,0.0017580071,0.000056325378,0.000094086376],"category_scores_gemma":[0.00077635405,0.00012741293,0.00003424481,0.00046627043,0.00008565389,0.0045756325,0.0007629751,0.00061130035,0.0000012173003],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00007983862,0.000075145916,0.93950975,0.00021880331,0.00012344886,0.0013223053,0.038258094,0.00046962308,0.0001990533,0.009789363,0.001540207,0.008414341],"study_design_scores_gemma":[0.000854567,0.000066661734,0.7428704,0.0020823267,0.000040200925,0.00042334737,0.109465465,0.1352666,0.000015304231,0.002246396,0.0061260588,0.00054268993],"about_ca_topic_score_codex":0.9848967,"about_ca_topic_score_gemma":0.9986765,"teacher_disagreement_score":0.19663939,"about_ca_system_score_codex":0.004980685,"about_ca_system_score_gemma":0.01301525,"threshold_uncertainty_score":0.99965197},"labels":[],"label_agreement":null},{"id":"W4402405330","doi":"10.23889/ijpds.v9i5.2592","title":"Towards a \"Biography\" of Population Health Data about Substance Use Disorders: Qualitative Approaches to Communicating Context","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Substance Abuse Treatment and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"British Columbia Environmental and Occupational Health Research Network; University Health Network; Dalhousie University; British Columbia Centre on Substance Use","funders":"","keywords":"Context (archaeology); Population; Population health; Data science; Computer science; Medicine; History; Environmental health","score_opus":0.4724267355289768,"score_gpt":0.4958945789099292,"score_spread":0.023467843380952425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405330","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9504209,0.0026201378,0.03120004,0.012199528,0.0013376172,0.0009060038,0.0011916785,0.00007658463,0.00004751197],"genre_scores_gemma":[0.954709,0.000377394,0.04033934,0.00033625468,0.00013020047,0.000009836974,0.0040235464,0.00001597921,0.000058450692],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99754983,0.00007935774,0.0006989644,0.00048403902,0.00095458614,0.00023319358],"domain_scores_gemma":[0.9979836,0.00036940354,0.00033555564,0.0008762123,0.00027708008,0.00015814595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024276124,0.00014188011,0.00026461834,0.00061829254,0.00025281784,0.00031116325,0.0016715239,0.000030968586,0.000013334509],"category_scores_gemma":[0.0008945935,0.00011477133,0.00007941269,0.0007768849,0.00014072946,0.003698133,0.00026761924,0.00015743118,0.0000030272427],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006567102,0.0003775346,0.585026,0.000112926915,0.00053855253,0.000007272031,0.025568932,0.00023311298,0.00021094654,0.06955069,0.0035870704,0.31413025],"study_design_scores_gemma":[0.0020316453,0.00032622286,0.90715206,0.002247854,0.0001291325,0.00008383746,0.010304998,0.063335456,0.00006546514,0.005120699,0.008828863,0.00037375867],"about_ca_topic_score_codex":0.0013489596,"about_ca_topic_score_gemma":0.0030989961,"teacher_disagreement_score":0.32212606,"about_ca_system_score_codex":0.00023775469,"about_ca_system_score_gemma":0.00021307282,"threshold_uncertainty_score":0.46802387},"labels":[],"label_agreement":null},{"id":"W4402405336","doi":"10.23889/ijpds.v9i5.2482","title":"Prevalence of dementia among people experiencing homelessness in Ontario, Canada: a population-based comparative analysis","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Lawson Health Research Institute","funders":"","keywords":"Dementia; Population; Gerontology; Psychiatry; Psychology; Medicine; Environmental health; Disease","score_opus":0.08746556609158386,"score_gpt":0.44872180864532313,"score_spread":0.3612562425537393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405336","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914524,0.00012224706,0.0056975256,0.000078659396,0.0019704625,0.0002844021,0.00031280433,0.00001342621,0.00006807328],"genre_scores_gemma":[0.9986767,0.000008756117,0.0006211861,0.000017309974,0.00010514754,0.00003512071,0.0004680662,0.0000060352836,0.000061673105],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99736094,0.000111640664,0.0008320973,0.00036828176,0.0010433823,0.00028367943],"domain_scores_gemma":[0.99821746,0.00041296793,0.0003933713,0.00025282128,0.00062436564,0.00009898801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014591243,0.00011184745,0.00034161078,0.0006877822,0.0005084577,0.000115665745,0.0010823079,0.000050053433,0.0004413082],"category_scores_gemma":[0.00026549373,0.000101617254,0.00006234679,0.0010769168,0.000058424168,0.0015662246,0.00016256026,0.00028788744,0.0000010060769],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019797026,0.000020422922,0.9789981,0.000052945896,0.000085223524,0.0000033164895,0.012880625,0.006131778,0.00001993391,0.0014812952,0.000017242373,0.0002892875],"study_design_scores_gemma":[0.0001907121,0.000008380243,0.90956366,0.00023433159,0.00008029629,1.5338284e-7,0.008752893,0.08077444,0.000013891247,0.0001882533,0.00009474604,0.00009822511],"about_ca_topic_score_codex":0.9730621,"about_ca_topic_score_gemma":0.9991672,"teacher_disagreement_score":0.07464266,"about_ca_system_score_codex":0.001354213,"about_ca_system_score_gemma":0.0026448884,"threshold_uncertainty_score":0.48320153},"labels":[],"label_agreement":null},{"id":"W4402405340","doi":"10.23889/ijpds.v9i5.2516","title":"Improving Responsiveness: Our Journey from Manual Yearly Updates to Automated Linkage for Near Real-Time Understanding of Outcomes and Modelling Future Service Demand","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Victoria Park","funders":"","keywords":"Linkage (software); Service (business); Computer science; Data science; Service model; Operations research; Process management; Operations management; Business; Engineering; Marketing","score_opus":0.04774687941578202,"score_gpt":0.34538380941593355,"score_spread":0.2976369300001515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405340","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.122662164,0.00007187708,0.872865,0.000902891,0.0017082193,0.00022697239,0.000835413,0.00071101135,0.000016425822],"genre_scores_gemma":[0.9287701,0.000093140115,0.07058041,0.000057220546,0.00021968035,0.000005530188,0.00023664582,0.00001652975,0.000020707104],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990426,0.000010091007,0.0002923974,0.00020713668,0.0003189448,0.00012883887],"domain_scores_gemma":[0.99949676,0.00006352083,0.000067404806,0.00013871392,0.00015976887,0.000073829324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007161754,0.000089979316,0.00010690366,0.00034012616,0.00015475016,0.00058622647,0.0005110338,0.000038824728,0.000002473527],"category_scores_gemma":[0.000067301335,0.000082833736,0.000028227858,0.00018525627,0.0000146514085,0.001509608,0.00012601494,0.00007906801,0.0000015002229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000489779,0.0000683983,0.0030369642,0.0005207936,0.00078989455,0.000031265976,0.0040309993,0.7959348,0.067041114,0.028358689,0.060135726,0.039561607],"study_design_scores_gemma":[0.00018323545,0.000022672717,0.0017904493,0.00013874337,0.000024544017,0.000007385783,0.00029708075,0.99489534,0.00017929175,0.0009337239,0.0014395232,0.00008799938],"about_ca_topic_score_codex":0.00008627949,"about_ca_topic_score_gemma":0.000023479088,"teacher_disagreement_score":0.806108,"about_ca_system_score_codex":0.00013334784,"about_ca_system_score_gemma":0.00004289682,"threshold_uncertainty_score":0.5652995},"labels":[],"label_agreement":null},{"id":"W4402405345","doi":"10.23889/ijpds.v9i5.2610","title":"Methodological Challenges when Using Routinely Collected Health Data for Research: A scoping review.","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Ottawa; University of Alberta; Alberta Health Services; University of Toronto; Simon Fraser University; AIDS Vancouver; Hospital for Sick Children","funders":"Economic and Social Research Council","keywords":"Data science; Data quality; Protocol (science); Computer science; Health informatics; Transparency (behavior); Informatics; Comparability; Research design; Management science; Medicine; Public health; Alternative medicine; Political science; Engineering; Nursing","score_opus":0.9332379448841444,"score_gpt":0.7226800341796469,"score_spread":0.21055791070449748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405345","genre_codex":"commentary","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019415913,0.110550836,0.26662,0.59125686,0.019199083,0.0054862807,0.0038443687,0.0002115994,0.0008893807],"genre_scores_gemma":[0.060110424,0.22327723,0.68263316,0.017002998,0.012002564,0.00015392376,0.0032594232,0.00008251745,0.0014777862],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957975,0.000633986,0.0007081069,0.00060707197,0.0016270243,0.00062628],"domain_scores_gemma":[0.9953672,0.0025997472,0.00024047267,0.00051014335,0.0009863821,0.00029602824],"candidate_categories":["metaresearch","sts"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.046793982,0.000087212706,0.00024641564,0.00036184263,0.0022055097,0.0009761829,0.0035491392,0.00004982237,0.00007619314],"category_scores_gemma":[0.030894693,0.00007317539,0.00005137437,0.0005225288,0.00027754562,0.0030098187,0.00070615706,0.00024465087,0.0000029657735],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016852116,0.00013363546,0.0016589995,0.0059688906,0.00011643688,0.000019241803,0.005100316,0.00011974389,0.000038663227,0.51456535,0.19189283,0.28021738],"study_design_scores_gemma":[0.00064411876,0.0001522057,0.0057577994,0.050013367,0.00004060875,0.00011582724,0.002806778,0.13739052,0.0000033394213,0.0511019,0.75153387,0.00043966377],"about_ca_topic_score_codex":0.0030350501,"about_ca_topic_score_gemma":0.00420178,"teacher_disagreement_score":0.57425386,"about_ca_system_score_codex":0.00061130745,"about_ca_system_score_gemma":0.003913897,"threshold_uncertainty_score":0.9990935},"labels":[],"label_agreement":null},{"id":"W4402405409","doi":"10.23889/ijpds.v9i5.2492","title":"Opioid-related overdose deaths among people experiencing homelessness, 2017 to 2021: A population-based analysis using coroner and health administrative data from Ontario, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Coroner; Opioid overdose; Population; Medicine; Population health; Opioid use disorder; Environmental health; Psychiatry; Medical emergency; Opioid; Suicide prevention; Poison control; (+)-Naloxone","score_opus":0.16973771602397755,"score_gpt":0.4977912438568011,"score_spread":0.3280535278328236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405409","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97928834,0.00018331321,0.012225835,0.0005428513,0.003644291,0.00042880853,0.003641986,0.00002223341,0.000022349917],"genre_scores_gemma":[0.9891859,0.000021250264,0.0030314005,0.00014632409,0.00047514553,0.000015295906,0.007023431,0.000016718011,0.000084505264],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966859,0.00013370095,0.0008789393,0.0007912525,0.0010936619,0.00041650957],"domain_scores_gemma":[0.99766475,0.00034559102,0.00047395244,0.0006286057,0.00052247965,0.00036460362],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001741378,0.00018219482,0.00043296357,0.00046751692,0.0018971643,0.00052013557,0.001503879,0.00007968933,0.0006506104],"category_scores_gemma":[0.00045657344,0.00016776017,0.00004285112,0.0009660411,0.00006844339,0.0024894474,0.0006028665,0.00032896723,0.0000036503707],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003238402,0.000019795982,0.98151904,0.000015157927,0.00017105766,0.000012925571,0.0145679,0.0012641894,0.000017639417,0.00044468048,0.0004533263,0.0014819119],"study_design_scores_gemma":[0.00022993726,0.000018530984,0.77420276,0.00025348592,0.0000778506,7.5041464e-7,0.009723613,0.2143199,0.000002098435,0.00023924262,0.0007674917,0.00016434777],"about_ca_topic_score_codex":0.9803323,"about_ca_topic_score_gemma":0.9978327,"teacher_disagreement_score":0.21305571,"about_ca_system_score_codex":0.002278095,"about_ca_system_score_gemma":0.0062081954,"threshold_uncertainty_score":0.9994257},"labels":[],"label_agreement":null},{"id":"W4402405414","doi":"10.23889/ijpds.v9i5.2506","title":"Population health value of being in target: Results from the Canadian Multi-Morbidity Model for Type 2 Diabetes","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Sunnybrook Health Science Centre; University of Ottawa","funders":"","keywords":"Type 2 diabetes; Value (mathematics); Population; Medicine; Diabetes mellitus; Population health; Computer science; Environmental health; Endocrinology; Machine learning","score_opus":0.5480469095290809,"score_gpt":0.5182949496367385,"score_spread":0.02975195989234236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405414","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6621287,0.001954412,0.13296376,0.15776913,0.011639864,0.0019439424,0.031461082,0.00004138316,0.00009775516],"genre_scores_gemma":[0.9619678,0.00005172973,0.033078134,0.0021594001,0.00041616874,0.00001313893,0.002248227,0.000012980837,0.00005237353],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965993,0.00007674885,0.002362304,0.0004510818,0.00022499108,0.0002855763],"domain_scores_gemma":[0.99736714,0.0008192687,0.0010919061,0.00035691762,0.00022524546,0.00013953364],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02140841,0.000092248425,0.00028494516,0.0005317106,0.00040617105,0.00034766537,0.0010645912,0.000053270665,0.000013973615],"category_scores_gemma":[0.008951538,0.00009230959,0.00005483189,0.00027586683,0.00005560015,0.0018952945,0.00007053968,0.00014115123,0.000013240112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006457365,0.00007374056,0.4363649,0.00010444966,0.000091577254,5.970244e-7,0.0038525176,0.17059615,0.000019140429,0.36677325,0.019549163,0.00250994],"study_design_scores_gemma":[0.00029481738,0.000013671524,0.16512845,0.000114087125,0.0000018004606,7.321236e-7,0.00004290005,0.7821963,0.000001505803,0.048185553,0.003946389,0.00007378539],"about_ca_topic_score_codex":0.1721256,"about_ca_topic_score_gemma":0.15295061,"teacher_disagreement_score":0.61160016,"about_ca_system_score_codex":0.0013738176,"about_ca_system_score_gemma":0.00091899646,"threshold_uncertainty_score":0.9993965},"labels":[],"label_agreement":null},{"id":"W4402405519","doi":"10.23889/ijpds.v9i5.2630","title":"Improving Detection of Hospital Adverse Events Using Machine Learning on Real-World Narrative EMR Data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Knowledge Management and Technology","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Libin Cardiovascular Institute of Alberta; University of Calgary; Alberta Health Services","funders":"","keywords":"Narrative; Real world data; Computer science; Data science; Artificial intelligence; Machine learning; Art; Literature","score_opus":0.16878099326327795,"score_gpt":0.4684002264340318,"score_spread":0.29961923317075384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405519","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8102557,0.000062628416,0.17635031,0.000722804,0.011618954,0.0002856842,0.00033586574,0.00007373198,0.00029429284],"genre_scores_gemma":[0.9949242,0.000014770723,0.0037636482,0.000012477817,0.00030976487,0.0000015208765,0.00018302925,0.000009388956,0.00078118895],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966559,0.000065413995,0.00067953405,0.00068519363,0.0017246999,0.00018926078],"domain_scores_gemma":[0.9977035,0.00032636698,0.0005464368,0.0007181738,0.0006458826,0.00005962718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049078185,0.00011264758,0.00014511315,0.0016640262,0.00045117585,0.0003348806,0.004171357,0.000035131798,0.00007265863],"category_scores_gemma":[0.0053797993,0.000088809065,0.0000541305,0.0012359328,0.00013296914,0.004632499,0.0015589078,0.00026311717,0.000021996808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024326873,0.00022008795,0.1050829,0.000022471278,0.0001805676,0.000041678497,0.0010789369,0.007373146,0.017840676,0.017764391,0.00054306246,0.84960884],"study_design_scores_gemma":[0.00024499325,0.00013080594,0.014592292,0.00008441871,0.000020596026,0.000012872699,0.00046146373,0.97159326,0.00048311992,0.006802852,0.005451226,0.00012207775],"about_ca_topic_score_codex":0.000386144,"about_ca_topic_score_gemma":0.0008377733,"teacher_disagreement_score":0.96422017,"about_ca_system_score_codex":0.00020381216,"about_ca_system_score_gemma":0.00012164592,"threshold_uncertainty_score":0.77514887},"labels":[],"label_agreement":null},{"id":"W4402405553","doi":"10.23889/ijpds.v9i5.2871","title":"Exploring variations in patient safety events across equity-deserving populations","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information","funders":"","keywords":"Equity (law); Business; Psychology; Actuarial science; Political science; Law","score_opus":0.5253456531672961,"score_gpt":0.47450302253362586,"score_spread":0.05084263063367023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405553","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44313148,0.0007948071,0.46269274,0.043778993,0.037997477,0.001126232,0.0068819444,0.00016330404,0.0034330504],"genre_scores_gemma":[0.99359554,0.00016769637,0.005236233,0.00022932781,0.00033636543,0.00002859947,0.00031100525,0.0000114365985,0.000083777115],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9981772,0.000014223841,0.0008462911,0.00041334372,0.00022538762,0.00032357857],"domain_scores_gemma":[0.9992017,0.000060993247,0.00021557782,0.00031258218,0.000109147295,0.00010000784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026510514,0.00008735961,0.00012242018,0.0006507327,0.00042160976,0.0005574722,0.0011173454,0.000026038288,0.000052687265],"category_scores_gemma":[0.0008318605,0.00009834137,0.000049385937,0.0005828126,0.000026447738,0.0051926593,0.00068104145,0.00016151486,0.000054104075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011052731,0.00004653947,0.017528517,0.00001892706,0.000019926181,0.000006866995,0.0011186026,0.0035086952,0.000006731485,0.9263785,0.00020908291,0.051146593],"study_design_scores_gemma":[0.00038787082,0.000039021594,0.36825994,0.00023462057,0.0000046197765,0.00003546512,0.00028218518,0.2660487,0.0000044549543,0.20790231,0.15652344,0.00027739094],"about_ca_topic_score_codex":0.0034941519,"about_ca_topic_score_gemma":0.0012149025,"teacher_disagreement_score":0.7184762,"about_ca_system_score_codex":0.00070672826,"about_ca_system_score_gemma":0.000077351855,"threshold_uncertainty_score":0.5375717},"labels":[],"label_agreement":null},{"id":"W4402405562","doi":"10.23889/ijpds.v9i5.2882","title":"Balancing Privacy and Precision: Evaluating Meta-Analysis for National Health Data Integration in Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Meta-analysis; Data science; Data integration; Data mining; Internet privacy; Computer security; Medicine","score_opus":0.8670855062200638,"score_gpt":0.7085032493344741,"score_spread":0.1585822568855897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405562","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1387832,0.0055765435,0.65804255,0.17341174,0.006917019,0.003516357,0.013430961,0.00006571909,0.00025590352],"genre_scores_gemma":[0.93358195,0.00012958274,0.06235512,0.0007702217,0.00034138683,0.000020508718,0.0025708016,0.000009758745,0.00022068825],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99459785,0.00007643562,0.00094482244,0.0007311561,0.00341357,0.0002361507],"domain_scores_gemma":[0.9910239,0.0058301487,0.00028003883,0.0006429065,0.0020188438,0.00020418613],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.026335672,0.00009983653,0.00034043743,0.00071550504,0.0002516081,0.0005093118,0.0015909937,0.000045021196,0.00010054298],"category_scores_gemma":[0.04312071,0.00007646514,0.00009827934,0.00081922155,0.00007584126,0.0019276895,0.000683274,0.0005401729,7.650095e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017308595,0.0005137894,0.23253757,0.0010998641,0.045060217,0.000097509794,0.0018141953,0.020369846,0.0023661337,0.16705129,0.040127095,0.48723164],"study_design_scores_gemma":[0.00037886895,0.00007655194,0.051404737,0.0001276783,0.001177449,0.000055439552,0.00009070603,0.926062,0.0000151134445,0.018299626,0.0022269767,0.00008485092],"about_ca_topic_score_codex":0.05938195,"about_ca_topic_score_gemma":0.5513602,"teacher_disagreement_score":0.90569216,"about_ca_system_score_codex":0.0012730035,"about_ca_system_score_gemma":0.009535552,"threshold_uncertainty_score":0.99607944},"labels":[],"label_agreement":null},{"id":"W4402405571","doi":"10.23889/ijpds.v9i5.2706","title":"Recommended Minimum Elements for Transparent Reporting of Multi-Jurisdiction Algorithm Feasibility Studies","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Law, AI, and Intellectual Property","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; Public Health Agency of Canada; University of Manitoba","funders":"","keywords":"Computer science; Jurisdiction; Algorithm; Data mining; Political science; Law","score_opus":0.4118999508886879,"score_gpt":0.49116248068003465,"score_spread":0.07926252979134674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405571","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0065455497,0.00031886267,0.98280585,0.0014549203,0.0081632715,0.00039544067,0.00023928247,0.000053315067,0.000023479917],"genre_scores_gemma":[0.69127786,0.0001607651,0.3077673,0.0001073291,0.0003490189,0.000021217682,0.00014344748,0.000009090657,0.00016396356],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968162,0.000037507172,0.0015557959,0.0005805759,0.0007794473,0.00023047288],"domain_scores_gemma":[0.99721414,0.00021292942,0.0008354172,0.00041912697,0.0012371741,0.000081186314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004911541,0.00011674099,0.00019787958,0.00028897318,0.00035165754,0.00047298142,0.0020526266,0.000030427627,0.000010228859],"category_scores_gemma":[0.0029152916,0.000089492794,0.00011194542,0.000334322,0.000120458666,0.0037699477,0.0003235572,0.000108634275,0.0000015311078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000104665814,0.00036315978,0.0036058452,0.00013424923,0.0003606938,0.000009964402,0.0026167273,0.0005240765,0.007116876,0.0067339246,0.010998512,0.9674313],"study_design_scores_gemma":[0.0004242805,0.00015251529,0.0013441523,0.00015119059,0.00001820654,0.00006048146,0.000105109684,0.98092324,0.0022579082,0.00664622,0.0077926605,0.00012402046],"about_ca_topic_score_codex":0.000027749034,"about_ca_topic_score_gemma":0.000022484135,"teacher_disagreement_score":0.9803992,"about_ca_system_score_codex":0.0002928686,"about_ca_system_score_gemma":0.00022688683,"threshold_uncertainty_score":0.45609707},"labels":[],"label_agreement":null},{"id":"W4402405577","doi":"10.23889/ijpds.v9i5.2792","title":"Health selection among outmigrants, return migrants and non-migrants in three subcohorts of international, interprovincial migrants and non-migrants in Manitoba, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health","funders":"","keywords":"Selection (genetic algorithm); Political science; Business; Economics; Demographic economics; Computer science","score_opus":0.032725303506635293,"score_gpt":0.3599623464838433,"score_spread":0.327237042977208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405577","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98794436,0.00082069595,0.0015756596,0.0015544195,0.0062318016,0.000796205,0.0009929516,0.00002151348,0.000062392595],"genre_scores_gemma":[0.99789166,0.00040254515,0.00053535425,0.0002565082,0.00040543568,0.000033975288,0.00038827898,0.000029943045,0.000056316774],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99556875,0.00010045606,0.0014996221,0.0009634537,0.0012356115,0.0006320978],"domain_scores_gemma":[0.99815017,0.00021433363,0.0005670555,0.00035380563,0.0003956774,0.00031893793],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0025805028,0.00030788002,0.000448455,0.0015329516,0.0002867927,0.00034756592,0.0012114532,0.00013711881,0.00004970378],"category_scores_gemma":[0.00037483036,0.00029903173,0.00006118275,0.00080174743,0.00022358629,0.0021620374,0.00020582396,0.0005347376,0.0000028429117],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036540363,0.00011415195,0.95089334,0.00007921343,0.00006108362,0.0000550207,0.0023522626,0.000044600343,0.0001372972,0.00020984847,0.0019774127,0.043710373],"study_design_scores_gemma":[0.0014160571,0.00011691659,0.95011055,0.00090503093,0.000015068563,0.00024254578,0.0008200282,0.044847492,0.000029391871,0.000592246,0.00066162186,0.00024303133],"about_ca_topic_score_codex":0.75166565,"about_ca_topic_score_gemma":0.9856734,"teacher_disagreement_score":0.23400775,"about_ca_system_score_codex":0.00068704924,"about_ca_system_score_gemma":0.0010833943,"threshold_uncertainty_score":0.9999462},"labels":[],"label_agreement":null},{"id":"W4402405587","doi":"10.23889/ijpds.v9i5.2889","title":"Assessing Hospital Data Quality: Application of a Data Quality Tool in 15 Countries","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Quality (philosophy); Data quality; Computer science; Data science; Business; Data mining; Marketing","score_opus":0.6479204626278048,"score_gpt":0.6713651621003011,"score_spread":0.023444699472496278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405587","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34229496,0.00034360567,0.6143856,0.022263182,0.009977267,0.0012460493,0.008947427,0.00010819254,0.00043372565],"genre_scores_gemma":[0.975015,0.0001241764,0.012331635,0.0005615564,0.00087017217,0.00001673322,0.011014086,0.000009597513,0.00005703411],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954144,0.00021374683,0.0018815271,0.0005481672,0.0016261579,0.00031600398],"domain_scores_gemma":[0.9955688,0.0011786979,0.0008973506,0.001525442,0.0007246681,0.00010501786],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.022719914,0.00010244784,0.00021320995,0.00041456148,0.0006004137,0.00036664787,0.0042834193,0.00009499673,0.00007191492],"category_scores_gemma":[0.0073000765,0.00008806608,0.00001887523,0.00046534644,0.00015107375,0.014496794,0.0015973473,0.0005244344,0.000031608906],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024002178,0.00021708109,0.34195226,0.0018488185,0.000074061056,0.000005867085,0.003485594,0.00019392345,0.00036846937,0.21665159,0.029997846,0.40496445],"study_design_scores_gemma":[0.00070980744,0.000029779661,0.26802132,0.0010196503,0.000018360572,0.00000835535,0.0014039282,0.5859879,0.000005274418,0.0068940455,0.13570088,0.00020064134],"about_ca_topic_score_codex":0.0015258333,"about_ca_topic_score_gemma":0.00051402126,"teacher_disagreement_score":0.63272005,"about_ca_system_score_codex":0.0003453145,"about_ca_system_score_gemma":0.0016270909,"threshold_uncertainty_score":0.99928695},"labels":[],"label_agreement":null},{"id":"W4402405591","doi":"10.23889/ijpds.v9i5.2698","title":"The Impact of COVID-19 on Mental Health Outcomes among Recipients of Ontario Social Assistance Benefits","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Social Sciences and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Centre for Addiction and Mental Health; SickKids Foundation","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Mental health; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Psychology; Medicine; Environmental health; Psychiatry; Virology; Disease; Outbreak","score_opus":0.13920323387336314,"score_gpt":0.5027628789523164,"score_spread":0.3635596450789533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405591","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9755553,0.00016223958,0.00043333814,0.016086858,0.0057230396,0.00028539813,0.0010586046,0.000016409984,0.00067881757],"genre_scores_gemma":[0.9984735,0.000111700574,0.00018550582,0.00008392759,0.00023783112,0.000002761004,0.000036916066,0.0000039246465,0.0008639257],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970935,0.000063488194,0.0004460321,0.00025877228,0.0018654265,0.00027280478],"domain_scores_gemma":[0.99857193,0.00024252266,0.00056942063,0.00015473901,0.0002833556,0.00017800534],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0038302592,0.00008084408,0.00013586745,0.0001226064,0.0018116366,0.00043893149,0.0019807282,0.00003183126,0.000053309854],"category_scores_gemma":[0.0013096485,0.000053728774,0.00013833024,0.00047496514,0.00069880905,0.0015207453,0.00012986806,0.00012598235,0.0000012353152],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009857564,0.000077483346,0.80673724,0.000004756444,0.000069487054,9.462784e-7,0.019375669,0.0006207122,0.000013819993,0.121006615,0.021061365,0.030933347],"study_design_scores_gemma":[0.00018341282,0.00007140648,0.96675336,0.00005496863,0.0000030574647,0.000001410612,0.0008316933,0.000753846,0.0000023121288,0.003807886,0.027465692,0.000070939604],"about_ca_topic_score_codex":0.26693377,"about_ca_topic_score_gemma":0.30608115,"teacher_disagreement_score":0.16001615,"about_ca_system_score_codex":0.0027800365,"about_ca_system_score_gemma":0.0045565753,"threshold_uncertainty_score":0.9994879},"labels":[],"label_agreement":null},{"id":"W4402405598","doi":"10.23889/ijpds.v9i5.2697","title":"Using linked administrative data to describe a cohort of young people who have a parent with a history of homelessness (Study 1)","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; University of Winnipeg","funders":"","keywords":"Cohort; Psychology; Demography; Gerontology; Developmental psychology; Sociology; Medicine","score_opus":0.36408111368496626,"score_gpt":0.5303430996289739,"score_spread":0.1662619859440076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405598","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98065263,0.00012703318,0.014307312,0.00011188581,0.002454833,0.0008826443,0.0012689739,0.0000152482435,0.00017942332],"genre_scores_gemma":[0.9968896,0.000021141565,0.0022483384,0.000011135189,0.00029213564,0.000027199654,0.00033710423,0.000013129563,0.00016020959],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972761,0.00012548223,0.00077772926,0.0004504449,0.0011398628,0.00023035432],"domain_scores_gemma":[0.997364,0.00021055924,0.0004728614,0.00056817156,0.0012544515,0.00012995781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024618728,0.00011676631,0.00038050575,0.0003724625,0.0003040234,0.00007882742,0.0019336856,0.000044662153,0.00005393969],"category_scores_gemma":[0.00061962474,0.0000927574,0.000028980507,0.00036129163,0.00012303158,0.0017750518,0.00066804053,0.00023209988,0.0000015930477],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019319447,0.00015831346,0.9438358,0.00008939418,0.000113194124,0.000008692284,0.051668074,0.0001580973,0.0003477722,0.0017919152,0.00019799513,0.001437559],"study_design_scores_gemma":[0.00057324115,0.00022424039,0.85654664,0.0010115323,0.00011099702,0.0000065062145,0.07711164,0.0627839,0.0000108743625,0.00018953695,0.001247106,0.00018378944],"about_ca_topic_score_codex":0.005893855,"about_ca_topic_score_gemma":0.027258754,"teacher_disagreement_score":0.087289155,"about_ca_system_score_codex":0.0007020148,"about_ca_system_score_gemma":0.0019355783,"threshold_uncertainty_score":0.9904912},"labels":[],"label_agreement":null},{"id":"W4402405604","doi":"10.23889/ijpds.v9i5.2820","title":"Expanding data resources beyond “health care”: exploring options and implications","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Health care; Data science; Business; Computer science; Risk analysis (engineering); Economics; Economic growth","score_opus":0.5693426971422808,"score_gpt":0.5715981845222683,"score_spread":0.0022554873799874864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405604","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.120019905,0.0068745622,0.7119804,0.1108698,0.02315352,0.0011832508,0.023595365,0.000286001,0.0020371622],"genre_scores_gemma":[0.96166706,0.0009887329,0.031964637,0.00076078874,0.0010432545,0.000025212317,0.0030938778,0.000015558719,0.00044086637],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962222,0.00007864156,0.00077036116,0.00091328187,0.0017645194,0.00025102214],"domain_scores_gemma":[0.9970414,0.0006111776,0.00027010002,0.0014429451,0.00043618988,0.00019815873],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.009484196,0.000102402235,0.0001313745,0.0009274553,0.001157893,0.005158786,0.006217192,0.000019112063,0.000049084578],"category_scores_gemma":[0.0032109998,0.000082959225,0.000031654654,0.00078339735,0.00018448487,0.0124253845,0.0029153503,0.00014978666,0.000026226196],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016082775,0.00003026588,0.0024228173,0.000015855292,0.000042658146,0.0000041442686,0.0024543735,0.00029597152,0.0001396362,0.1809204,0.051819444,0.7618383],"study_design_scores_gemma":[0.00021470568,0.000039199866,0.039782528,0.000109322325,0.000020506483,0.000107986416,0.004902321,0.027303975,0.000009997244,0.045606297,0.8817113,0.0001918554],"about_ca_topic_score_codex":0.00016754871,"about_ca_topic_score_gemma":0.000252006,"teacher_disagreement_score":0.84164715,"about_ca_system_score_codex":0.00017460997,"about_ca_system_score_gemma":0.00022287772,"threshold_uncertainty_score":0.99915963},"labels":[],"label_agreement":null},{"id":"W4402405605","doi":"10.23889/ijpds.v9i5.2799","title":"Cycling and Pedestrian Injuries in the Region of Peel, Ontario; An application of linked administrative health data to enhance local road safety and health service delivery, through an Applied Health Research Question (AHRQ)","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Traffic and Road Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Health services; Pedestrian; Business; Occupational safety and health; Cycling; Service (business); Service delivery framework; Environmental health; Engineering; Medicine; Geography; Marketing","score_opus":0.25222384237370726,"score_gpt":0.5038469445882638,"score_spread":0.2516231022145566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5150855,0.0007152762,0.46730015,0.0146102505,0.00045825113,0.0010919654,0.00066662434,0.000044483844,0.000027480446],"genre_scores_gemma":[0.98913413,0.0007437782,0.0087783765,0.00017468345,0.00010881934,0.000006984075,0.0010427092,0.000008684855,0.0000018463375],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978791,0.00013088321,0.00069034763,0.00041591766,0.00066606776,0.0002177008],"domain_scores_gemma":[0.998888,0.000110554596,0.0001937194,0.00044817087,0.0002242289,0.00013533056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005571943,0.00009695468,0.00017922427,0.00024184935,0.00031352037,0.00015460237,0.0010522803,0.000035971392,8.862121e-7],"category_scores_gemma":[0.000060522536,0.00008105221,0.0000085982165,0.00048496024,0.00013817076,0.0021809589,0.00018238976,0.0003043058,2.7745276e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054036273,0.00017918415,0.0055556567,0.00048373832,0.000035154648,0.0000021346027,0.031034825,0.040911846,0.00038087094,0.036172215,0.00034425288,0.8843598],"study_design_scores_gemma":[0.00036804244,0.0005693288,0.45645943,0.00061532034,0.000005607097,0.00008138098,0.004355998,0.53200483,0.000036819794,0.0016661487,0.0036731209,0.00016399636],"about_ca_topic_score_codex":0.028930206,"about_ca_topic_score_gemma":0.13020279,"teacher_disagreement_score":0.88419574,"about_ca_system_score_codex":0.00038760508,"about_ca_system_score_gemma":0.000837686,"threshold_uncertainty_score":0.97753626},"labels":[],"label_agreement":null},{"id":"W4402405615","doi":"10.23889/ijpds.v9i5.2823","title":"A game of snakes and ladders: the world of complex health and social care data linkage","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Future Earth","funders":"","keywords":"Linkage (software); Data science; Computer science; Genetics; Biology; Gene","score_opus":0.2465920220017384,"score_gpt":0.5016177145755112,"score_spread":0.2550256925737728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405615","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82259756,0.015854485,0.013192493,0.12257734,0.0046566674,0.0022872277,0.015315569,0.000102777274,0.003415895],"genre_scores_gemma":[0.9968404,0.00012937281,0.0010476867,0.00019447859,0.00020691854,8.6460574e-7,0.0015097572,0.000003875793,0.00006663435],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99896634,0.0000141820465,0.00025233816,0.00019519875,0.00048936525,0.00008257074],"domain_scores_gemma":[0.9993576,0.0000696904,0.00013975694,0.00023704217,0.00015004737,0.000045880253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061224797,0.000048118665,0.0000967819,0.00019681221,0.00011061746,0.00017694785,0.00062523823,0.000007620731,0.000025220312],"category_scores_gemma":[0.00011755959,0.000033445882,0.000015733438,0.00015665285,0.00029028428,0.00083457015,0.00045010512,0.00006851733,2.2256701e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006447729,0.000275931,0.060030367,0.0045041777,0.00090105674,0.000045193185,0.0122753475,0.00018622247,0.0015049154,0.3207352,0.09291957,0.5059773],"study_design_scores_gemma":[0.003130303,0.00037968843,0.52773875,0.002278841,0.00032291026,0.0002595879,0.0180365,0.25897545,0.0000436799,0.008866984,0.1796795,0.00028777422],"about_ca_topic_score_codex":0.00009901105,"about_ca_topic_score_gemma":0.00016470521,"teacher_disagreement_score":0.5056895,"about_ca_system_score_codex":0.000046614274,"about_ca_system_score_gemma":0.00031004078,"threshold_uncertainty_score":0.17063121},"labels":[],"label_agreement":null},{"id":"W4402405616","doi":"10.23889/ijpds.v9i5.2699","title":"Outcomes in clinical subgroups of patients with alcohol-related hospitalizations: a population-based retrospective cohort study","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Alcohol Consumption and Health Effects","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba; Centre for Addiction and Mental Health","funders":"","keywords":"Retrospective cohort study; Medicine; Cohort; Population; Demography; Cohort study; Emergency medicine; Internal medicine; Environmental health","score_opus":0.0855331260647901,"score_gpt":0.4717210127966083,"score_spread":0.38618788673181814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405616","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99392325,0.000028120656,0.0016496363,0.0006148807,0.001987534,0.0015021436,0.0002273907,0.000038367107,0.000028659593],"genre_scores_gemma":[0.9972617,0.000010519656,0.0011586339,0.0001445367,0.000074059186,0.00002514089,0.0012645278,0.000016739988,0.000044125674],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967282,0.00007510605,0.001074272,0.00049868046,0.0014339123,0.00018986595],"domain_scores_gemma":[0.9977972,0.00026072908,0.00037678386,0.0003795197,0.0010448495,0.0001409138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027407587,0.00013202976,0.0003430306,0.0008377968,0.00014935073,0.00014013084,0.00048970076,0.000059832862,0.000073567535],"category_scores_gemma":[0.0019971724,0.00009955475,0.000073579926,0.00072417525,0.00011741218,0.0011802485,0.00008010593,0.00027364754,0.0000055035707],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019674117,0.00060927175,0.99659926,0.000019374886,0.00010557677,0.000010484365,0.000057178753,0.0001796577,0.0000016487261,0.0010789235,0.00006005381,0.0010818589],"study_design_scores_gemma":[0.0027868182,0.00042445413,0.9708003,0.00021969277,0.000078524536,0.000006964783,0.000024104855,0.025285421,8.237057e-7,0.00022559741,0.000047896272,0.00009943218],"about_ca_topic_score_codex":0.00031701924,"about_ca_topic_score_gemma":0.00019519174,"teacher_disagreement_score":0.02579896,"about_ca_system_score_codex":0.00048726087,"about_ca_system_score_gemma":0.0004183767,"threshold_uncertainty_score":0.4059725},"labels":[],"label_agreement":null},{"id":"W4402405621","doi":"10.23889/ijpds.v9i5.2869","title":"COVID-19 Policy Decisions in Manitoba and the Experiences of the Red River Métis: A partnership-based, whole-population linked administrative data study","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Social Sciences and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; University of Manitoba","funders":"","keywords":"General partnership; Coronavirus disease 2019 (COVID-19); Population; Pandemic; Geography; Environmental planning; Business; Environmental health; Medicine; Disease; Finance; Infectious disease (medical specialty)","score_opus":0.2687832672532133,"score_gpt":0.5142158768485334,"score_spread":0.24543260959532015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9461609,0.00023110265,0.0019977905,0.046970308,0.002995756,0.0010846544,0.00035912625,0.000023193135,0.00017717874],"genre_scores_gemma":[0.9985599,0.00006802114,0.0003925737,0.00032815605,0.00047544803,0.000026647196,0.00004784016,0.000004014546,0.00009739511],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966778,0.00032651762,0.00048394417,0.00047295916,0.00179015,0.00024860908],"domain_scores_gemma":[0.99764645,0.001119928,0.00036091483,0.00049582374,0.00021204421,0.0001648678],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.006700325,0.000095797004,0.0001328576,0.00020694343,0.0013732187,0.000868595,0.0042209947,0.000041104788,0.00001795651],"category_scores_gemma":[0.01626091,0.000057751615,0.000044383407,0.0013412348,0.0016071574,0.002735397,0.00062622136,0.00016717415,8.6493554e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004984155,0.00033527936,0.4492122,0.000012616054,0.00007077761,0.000023315288,0.27684695,0.0015003759,0.000036404326,0.22694781,0.0072494596,0.037266403],"study_design_scores_gemma":[0.0019531313,0.00009916124,0.6414789,0.00021482502,0.00004478976,0.000018259274,0.20391978,0.06351998,0.000004024673,0.046205554,0.042268798,0.00027282082],"about_ca_topic_score_codex":0.0473906,"about_ca_topic_score_gemma":0.10505501,"teacher_disagreement_score":0.19226669,"about_ca_system_score_codex":0.00037996066,"about_ca_system_score_gemma":0.0023929155,"threshold_uncertainty_score":0.99992687},"labels":[],"label_agreement":null},{"id":"W4402405629","doi":"10.23889/ijpds.v9i5.2833","title":"Implementation of a common data model in Health Data Research Network Canada: Lessons learned","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Data science; Health data; Data mining; Health care; Political science","score_opus":0.726837005989322,"score_gpt":0.6996325491815134,"score_spread":0.027204456807808586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405629","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05319304,0.0055720233,0.06576885,0.7554292,0.026690464,0.004263108,0.08773262,0.00012630277,0.0012243836],"genre_scores_gemma":[0.96663254,0.0013678059,0.0080486145,0.0034844826,0.0009088727,0.000018041477,0.019224463,0.000023011287,0.0002921821],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99527794,0.00037332592,0.0012915139,0.0006424435,0.0017090685,0.00070569204],"domain_scores_gemma":[0.99636084,0.00090432435,0.00041277235,0.0015795146,0.0005631289,0.0001794012],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.020745764,0.00009384119,0.00022617161,0.00048065226,0.0011101644,0.000117606025,0.00594861,0.000047260794,0.000085334155],"category_scores_gemma":[0.0008795889,0.00008493721,0.00001413831,0.0007656913,0.00008738133,0.0033792928,0.0039413306,0.00077638734,0.0000041013946],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009841924,0.000044537028,0.08555195,0.00028590363,0.00004016403,0.000012800405,0.0005714566,0.003402729,0.00002663954,0.042853743,0.73718315,0.12992848],"study_design_scores_gemma":[0.0005986961,0.000035533565,0.06597941,0.0004584785,0.000008011267,0.000010785981,0.0011253007,0.69885105,0.0000012659341,0.010148984,0.22266349,0.00011899023],"about_ca_topic_score_codex":0.61397713,"about_ca_topic_score_gemma":0.9194897,"teacher_disagreement_score":0.9134395,"about_ca_system_score_codex":0.0020506845,"about_ca_system_score_gemma":0.027298933,"threshold_uncertainty_score":0.9994297},"labels":[],"label_agreement":null},{"id":"W4402405633","doi":"10.23889/ijpds.v9i5.2694","title":"Evidence from an Applied Health Research Question (AHRQ): Describing Bundled Care Use in Ontario among Individuals with Total Joint Arthroplasty from fiscal year 2018-2021.","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Joint arthroplasty; Joint (building); Arthroplasty; Medicine; Health care; Family medicine; Physical therapy; Surgery; Economics; Engineering; Economic growth","score_opus":0.6376221179359266,"score_gpt":0.5567085475398958,"score_spread":0.08091357039603075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405633","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97810006,0.00009237214,0.016539391,0.0025674815,0.0014590168,0.0006454316,0.0005611829,0.000024613555,0.000010472234],"genre_scores_gemma":[0.95391893,0.000050826704,0.040860113,0.00015890154,0.00069446553,0.000016843844,0.0042414605,0.000017988426,0.00004045003],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9953658,0.00019936833,0.0010703021,0.0007721664,0.0022537953,0.00033855313],"domain_scores_gemma":[0.99698704,0.0011605519,0.00033767906,0.00047875647,0.0007438168,0.00029213633],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0055853464,0.00014192845,0.00022340851,0.0006142316,0.0003007065,0.0012329185,0.0005137274,0.000065910484,0.00028036645],"category_scores_gemma":[0.004753029,0.00012003266,0.00003879185,0.0004375736,0.00019385564,0.0068415566,0.00031404992,0.0008444308,0.000023019504],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005464891,0.0001029787,0.96670896,0.00000936647,0.00005111548,0.00003548538,0.0021928055,0.0010667273,0.0008485721,0.00025150034,0.0008905978,0.02729539],"study_design_scores_gemma":[0.0011156452,0.00032423,0.9732725,0.0017466315,0.000034967594,0.000044185203,0.0019247179,0.020230466,0.00006331692,0.0005697478,0.00054326246,0.00013031634],"about_ca_topic_score_codex":0.19080594,"about_ca_topic_score_gemma":0.38864684,"teacher_disagreement_score":0.1978409,"about_ca_system_score_codex":0.0019438165,"about_ca_system_score_gemma":0.0016456908,"threshold_uncertainty_score":0.9998039},"labels":[],"label_agreement":null},{"id":"W4402405640","doi":"10.23889/ijpds.v9i5.2802","title":"Linked administrative health data on prehospital olanzapine administration by paramedics in Winnipeg, Canada: Challenges and opportunities","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Winnipeg; University of Manitoba; Manitoba Health","funders":"","keywords":"Administration (probate law); Olanzapine; Medical emergency; Medicine; Business; Schizophrenia (object-oriented programming); Psychiatry; Political science","score_opus":0.3937303475181009,"score_gpt":0.5363967414399343,"score_spread":0.14266639392183345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405640","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10491633,0.021407573,0.0022278891,0.8231293,0.021715904,0.0022382336,0.021809723,0.0001363367,0.002418718],"genre_scores_gemma":[0.96680003,0.01219896,0.0010923764,0.010505527,0.000951754,0.000025972675,0.0077635376,0.000018973149,0.0006428382],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99727243,0.00013586889,0.00079438847,0.00051559875,0.00091746706,0.00036422993],"domain_scores_gemma":[0.9981504,0.0005967381,0.00031598838,0.00044575572,0.00023012332,0.00026099614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029638298,0.00013444222,0.00020083996,0.00024722132,0.00053685246,0.0001303826,0.0012957533,0.00006545266,0.000037134116],"category_scores_gemma":[0.0008040544,0.00011575684,0.000012716375,0.00011063331,0.00010247921,0.0021289634,0.00037231037,0.00052486046,0.0000023876678],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038560267,0.00014949834,0.008161424,0.0004913466,0.00008555015,0.00015941223,0.0027093603,0.000010907242,0.000025056412,0.07446827,0.49061564,0.42273793],"study_design_scores_gemma":[0.00088491867,0.0005127846,0.12093308,0.00091693894,0.0000136290255,0.00011831482,0.0030621102,0.013260866,0.000002388545,0.0025986156,0.85740113,0.0002952115],"about_ca_topic_score_codex":0.021478804,"about_ca_topic_score_gemma":0.21220641,"teacher_disagreement_score":0.86188376,"about_ca_system_score_codex":0.0010701647,"about_ca_system_score_gemma":0.013051842,"threshold_uncertainty_score":0.9925432},"labels":[],"label_agreement":null},{"id":"W4402405672","doi":"10.23889/ijpds.v9i5.2758","title":"Data Quality Implications in Research when Transitioning to a New Electronic Medical Record","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; Alberta Health","funders":"","keywords":"Quality (philosophy); Electronic medical record; Data quality; Computer science; Data science; Business; Internet privacy; Marketing","score_opus":0.7950921562511286,"score_gpt":0.6891429991574641,"score_spread":0.10594915709366448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405672","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017567823,0.0001081076,0.8088138,0.16696188,0.0030546277,0.00046998,0.002317967,0.00004445776,0.00066136423],"genre_scores_gemma":[0.943832,0.00019144677,0.045409992,0.00250774,0.0017908945,0.000033501165,0.0035052288,0.000022340779,0.002706873],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9910117,0.00034229143,0.0012462434,0.0011812999,0.005722623,0.00049588224],"domain_scores_gemma":[0.99459374,0.001962543,0.00015767278,0.002007676,0.0008642442,0.00041411398],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.06448714,0.00009622802,0.00015803988,0.0016979122,0.00044802186,0.0034728807,0.013950976,0.00004952095,0.00061116554],"category_scores_gemma":[0.027433882,0.00008042308,0.00004078944,0.0021567035,0.00014961608,0.0074740513,0.002569062,0.00049635005,0.00018541403],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005465957,0.00005570337,0.0015589201,0.000003961621,0.000017769959,0.000007878547,0.00040074508,0.00013956007,0.00014158581,0.29131266,0.15313664,0.5531699],"study_design_scores_gemma":[0.00021375877,0.00003498851,0.019567078,0.000100856174,0.0000041217013,0.00003869272,0.00030395892,0.031593006,0.000004994936,0.31638128,0.63164645,0.0001108149],"about_ca_topic_score_codex":0.0021693576,"about_ca_topic_score_gemma":0.012139637,"teacher_disagreement_score":0.92626417,"about_ca_system_score_codex":0.00043968394,"about_ca_system_score_gemma":0.0017965533,"threshold_uncertainty_score":0.99756163},"labels":[],"label_agreement":null},{"id":"W4402405684","doi":"10.23889/ijpds.v9i5.2760","title":"Reporting on the establishment of a Privacy Preserving Record Linkage to Facilitate an Ongoing Crosswalk Between Research and Health Administrative Databases","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Indoc Research; Ontario Brain Institute","funders":"","keywords":"Schema crosswalk; Record linkage; Linkage (software); Database; Data science; Computer science; Internet privacy; Data mining; Business; Medicine; Engineering; Environmental health; Transport engineering","score_opus":0.9109178340257105,"score_gpt":0.6727323830946649,"score_spread":0.2381854509310456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405684","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8729688,0.00006272398,0.0783184,0.042497046,0.0015587402,0.00085150276,0.0033514863,0.000026322057,0.0003650106],"genre_scores_gemma":[0.9868198,0.000026771106,0.01188766,0.00026076933,0.0002495353,0.000011489989,0.00028907892,0.000005856443,0.0004490145],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9932593,0.0002801639,0.001757249,0.00078377395,0.0036200576,0.00029945164],"domain_scores_gemma":[0.993659,0.0028497535,0.00097388297,0.0011531757,0.0011277501,0.000236404],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.06985871,0.000094416304,0.00018307875,0.0007846038,0.0008914953,0.0035875791,0.0038884936,0.000014552462,0.000047748363],"category_scores_gemma":[0.035505973,0.0000609864,0.000032080814,0.0010235145,0.00023822098,0.005406113,0.0022401514,0.0002666804,0.000008307293],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019161639,0.00021381005,0.066111736,0.00008625077,0.00009549926,0.000036885376,0.009235814,0.0005274934,0.00054585614,0.14943387,0.058815822,0.71470535],"study_design_scores_gemma":[0.0003920547,0.0015037633,0.4259354,0.0016207147,0.000014649196,0.000055362303,0.010629838,0.041163288,0.0006195438,0.112357154,0.40534508,0.00036316054],"about_ca_topic_score_codex":0.001388872,"about_ca_topic_score_gemma":0.0006335622,"teacher_disagreement_score":0.7143422,"about_ca_system_score_codex":0.00016780841,"about_ca_system_score_gemma":0.0004475631,"threshold_uncertainty_score":0.9974468},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low"}],"label_agreement":"split"},{"id":"W4402405698","doi":"10.23889/ijpds.v9i5.2759","title":"Automated Translation of Chronic Disease Diagnosis Codes using the ChatGPT Large Language Model","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Translation (biology); Computer science; Natural language processing; Artificial intelligence; Biology; Genetics","score_opus":0.31777447285582566,"score_gpt":0.5882422206241901,"score_spread":0.2704677477683644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405698","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7720582,0.0023165508,0.20520002,0.006968468,0.0076148184,0.0011458534,0.0044279895,0.00021907972,0.000049043854],"genre_scores_gemma":[0.9964847,0.00013439391,0.0020513036,0.00017099983,0.0007145104,0.00003383537,0.00034963133,0.00001542663,0.000045226265],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977486,0.00011990658,0.00070212036,0.00028977252,0.000825474,0.0003140898],"domain_scores_gemma":[0.9980965,0.0005387819,0.00028141984,0.0003668155,0.0005926634,0.00012376781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025313795,0.000094233576,0.00011035141,0.000282476,0.0010582657,0.00011820795,0.0012335266,0.00005166641,0.00011203618],"category_scores_gemma":[0.00094485824,0.00006777508,0.00005762106,0.0003906569,0.0001294233,0.0017998738,0.00018807806,0.0003007433,0.000011496114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005518604,0.0004354743,0.2508958,0.0013249882,0.00026422666,0.000060047638,0.033276126,0.38973224,0.01620952,0.14335136,0.009994533,0.15390383],"study_design_scores_gemma":[0.00008200587,0.000013091005,0.003229447,0.0004930114,0.000024856708,0.000003987988,0.000682431,0.99140775,0.000101343656,0.0023735494,0.0015182176,0.00007033287],"about_ca_topic_score_codex":0.00081292976,"about_ca_topic_score_gemma":0.0009803289,"teacher_disagreement_score":0.60167545,"about_ca_system_score_codex":0.000458572,"about_ca_system_score_gemma":0.0012032726,"threshold_uncertainty_score":0.8139431},"labels":[],"label_agreement":null},{"id":"W4402405700","doi":"10.23889/ijpds.v9i5.2768","title":"Identifying a Birth Cohort of Twins from Linked Data – Challenges and Opportunities","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; Centre for Global Health Research","funders":"","keywords":"Cohort; Data science; Computer science; Medicine; Internal medicine","score_opus":0.26353636749617987,"score_gpt":0.407618993704224,"score_spread":0.14408262620804413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405700","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9572704,0.0022805168,0.028977223,0.0043285727,0.0026304047,0.00040710243,0.0031202822,0.00004749791,0.0009380412],"genre_scores_gemma":[0.9860745,0.0058963336,0.006907618,0.00015520441,0.0002127755,0.0000033381577,0.00064770004,0.0000120312325,0.00009047986],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99768674,0.000045297355,0.00039611425,0.00067870895,0.0010020786,0.00019102919],"domain_scores_gemma":[0.99885744,0.00019779985,0.00018419125,0.00058623013,0.00003642729,0.00013793663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002656407,0.00010002125,0.00011344086,0.00018130372,0.00020557058,0.0002929985,0.0018751984,0.000031512227,0.00026572915],"category_scores_gemma":[0.00044964429,0.000092407776,0.000019147861,0.000098759956,0.00034528848,0.004952137,0.0016506372,0.00015274335,0.000017708728],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040364142,0.000086155334,0.1031383,0.000051529827,0.00013612362,0.00007589591,0.0017381466,0.00023899577,0.009675726,0.004682204,0.0010199279,0.87911665],"study_design_scores_gemma":[0.00024005202,0.00003219532,0.8086226,0.00026391828,0.000042556418,0.00013150512,0.00060938875,0.13093266,0.000100959085,0.008045686,0.050769333,0.00020913292],"about_ca_topic_score_codex":0.00055709964,"about_ca_topic_score_gemma":0.00020507231,"teacher_disagreement_score":0.8789075,"about_ca_system_score_codex":0.00015726767,"about_ca_system_score_gemma":0.000069688926,"threshold_uncertainty_score":0.37682799},"labels":[],"label_agreement":null},{"id":"W4402405709","doi":"10.23889/ijpds.v9i5.2755","title":"Roadmap for Linking Registry Data with Health Services Data to Support Evidence-Informed Decision-Making.","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Agency for Drugs and Technologies in Health","funders":"","keywords":"Business; Decision support system; Data science; Knowledge management; Process management; Computer science; Data mining","score_opus":0.5105961349505728,"score_gpt":0.6361266784025941,"score_spread":0.1255305434520213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405709","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030289028,0.00096272264,0.8731843,0.03562732,0.028195692,0.004663442,0.026678985,0.0002881558,0.000110347784],"genre_scores_gemma":[0.7149328,0.00029524032,0.26271695,0.0054418235,0.0041826926,0.000086036365,0.012022846,0.0000618671,0.00025974985],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9941247,0.00009682418,0.0016496782,0.0013591987,0.00196668,0.0008029294],"domain_scores_gemma":[0.99025327,0.0035212266,0.0008530933,0.0032361276,0.0016823305,0.00045393693],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.010025983,0.00022066543,0.00028771206,0.00063477474,0.0023248594,0.0009024107,0.012642612,0.0001110714,0.00014236994],"category_scores_gemma":[0.0058836495,0.00017491881,0.00003579532,0.00077737786,0.00012128929,0.011164872,0.003965946,0.0006041289,0.00010670163],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007208393,0.00004799539,0.037051797,0.0009800021,0.00007969184,0.000027817972,0.0033796183,0.00076259923,0.000024947465,0.0034695563,0.077204145,0.876251],"study_design_scores_gemma":[0.00020398214,0.00031483496,0.0049521774,0.016281277,0.000033023127,0.00012817526,0.00364931,0.6655394,0.0000044629805,0.004161726,0.30440977,0.0003218773],"about_ca_topic_score_codex":0.0016054774,"about_ca_topic_score_gemma":0.0151465805,"teacher_disagreement_score":0.8759291,"about_ca_system_score_codex":0.0008926206,"about_ca_system_score_gemma":0.0065941047,"threshold_uncertainty_score":0.99903756},"labels":[],"label_agreement":null},{"id":"W4402405720","doi":"10.23889/ijpds.v9i5.2736","title":"Uptake of COVID-19 vaccinations amongst 3,433,483 children and young people across four nations in the UK","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Global Health Research","funders":"Economic and Social Research Council","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Vaccination; Geography; Medicine; Virology; Outbreak; Disease","score_opus":0.06391886230528905,"score_gpt":0.42786736754451793,"score_spread":0.3639485052392289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405720","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9608891,0.00032968874,0.01417089,0.020053513,0.0023839977,0.00049972796,0.001057492,0.0000308772,0.0005847357],"genre_scores_gemma":[0.99799496,0.00029997557,0.0007493055,0.0001633434,0.00039713547,0.000009812289,0.00017518378,0.0000050404183,0.00020527208],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99812186,0.00006305202,0.0003937953,0.00027517512,0.00092828943,0.0002178565],"domain_scores_gemma":[0.99885654,0.00032775424,0.00015615788,0.00020570142,0.00034786708,0.00010599861],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00373683,0.00007455897,0.000089737216,0.00040711506,0.0012603786,0.0010084637,0.0016272911,0.000037980248,0.000078028446],"category_scores_gemma":[0.0034140258,0.00005992929,0.000044009445,0.0009974359,0.000059153805,0.002541057,0.00017199782,0.00015121458,0.0000028161332],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016064367,0.000055879762,0.7346795,0.000010805397,0.00003156333,0.000007563539,0.01951096,0.0004020205,0.00004992216,0.23212732,0.005775322,0.0073330435],"study_design_scores_gemma":[0.00026256213,0.000015605987,0.97446114,0.00003424198,0.000012788175,0.00009026689,0.0023576934,0.003534948,0.000002245644,0.011989724,0.0071546403,0.00008414894],"about_ca_topic_score_codex":0.003808746,"about_ca_topic_score_gemma":0.059196074,"teacher_disagreement_score":0.2397816,"about_ca_system_score_codex":0.0002055839,"about_ca_system_score_gemma":0.00056764536,"threshold_uncertainty_score":0.9724638},"labels":[],"label_agreement":null},{"id":"W4402405728","doi":"10.23889/ijpds.v9i5.2734","title":"Prevalence and characteristics of people with a high body mass index across the kidney disease spectrum: a population-based cohort study","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Dialysis and Renal Disease Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Body mass index; Cohort; Population; Medicine; Disease; Cohort study; Demography; Index (typography); Kidney disease; Environmental health; Internal medicine; Computer science; World Wide Web","score_opus":0.015507379980388853,"score_gpt":0.33796036647314115,"score_spread":0.3224529864927523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405728","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9887737,0.000037290913,0.0062618754,0.0025110103,0.00068144104,0.0007507325,0.0009583859,0.000016361104,0.000009199176],"genre_scores_gemma":[0.99857897,0.000029579234,0.00026760108,0.00015516537,0.00022264672,0.00002405299,0.00060851773,0.000009929232,0.000103523314],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978386,0.000029464794,0.00036974557,0.00036049465,0.0012498036,0.00015185753],"domain_scores_gemma":[0.9988443,0.000073844,0.00019967523,0.00038212797,0.00028080324,0.00021920509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011786968,0.000105950385,0.00015517241,0.00019547161,0.00023229528,0.0004822315,0.000561825,0.000012905725,0.000045102697],"category_scores_gemma":[0.00046688717,0.00006260675,0.000044046457,0.00033669738,0.00010541397,0.00063580985,0.00015224176,0.00010125679,0.0000012552541],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029308922,0.00015447685,0.9973123,0.00009493232,0.0001320156,0.000024712113,0.00006508813,0.00023421587,0.000028354289,0.00073111727,0.00010158674,0.0008281018],"study_design_scores_gemma":[0.00050227204,0.00009631777,0.9145611,0.0002678824,0.00026798315,0.00001223453,0.000046990113,0.08376346,0.00000310478,0.00025418776,0.00015345411,0.000071046066],"about_ca_topic_score_codex":0.00031327034,"about_ca_topic_score_gemma":0.000034711637,"teacher_disagreement_score":0.08352924,"about_ca_system_score_codex":0.00010000176,"about_ca_system_score_gemma":0.00025685295,"threshold_uncertainty_score":0.46501696},"labels":[],"label_agreement":null},{"id":"W4402405750","doi":"10.23889/ijpds.v9i5.2733","title":"How is ‘shortage’ defined? Exploring Nursing Workforce Data across Canada 2015-2022: An Ecological Study","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Workforce; Economic shortage; Business; Nursing; Ecology; Environmental resource management; Medicine; Environmental science; Economics; Economic growth; Biology; Government (linguistics)","score_opus":0.4165481501794222,"score_gpt":0.5862129608619435,"score_spread":0.16966481068252132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94645923,0.0006550985,0.0033380142,0.015542837,0.028624581,0.0011947183,0.003845349,0.00013777419,0.00020241759],"genre_scores_gemma":[0.9918692,0.00011716993,0.002547821,0.000781339,0.0020055524,0.000045882807,0.0016915102,0.000027452157,0.0009140754],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99494725,0.00019347288,0.00086839445,0.0010521672,0.002020292,0.0009184009],"domain_scores_gemma":[0.9966508,0.0004911944,0.0003470779,0.0013177064,0.00073401094,0.00045922116],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003990116,0.00021754135,0.00024648843,0.0001642552,0.002568183,0.001015687,0.0052312952,0.0000848599,0.00015846494],"category_scores_gemma":[0.0016015471,0.00018369385,0.000031499738,0.00068145385,0.00013101721,0.008715963,0.0013550383,0.00078849564,0.000015826883],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033371625,0.0007384569,0.48467252,0.00011055096,0.0001534259,0.00034115347,0.010007125,0.0009195205,0.00008608652,0.012385161,0.20714954,0.28310272],"study_design_scores_gemma":[0.0011418186,0.0003134803,0.2625233,0.0018653529,0.00007448208,0.0001507052,0.04761273,0.1557001,0.0000089925015,0.0021888798,0.527754,0.0006661561],"about_ca_topic_score_codex":0.05524253,"about_ca_topic_score_gemma":0.27530825,"teacher_disagreement_score":0.32060444,"about_ca_system_score_codex":0.0017394791,"about_ca_system_score_gemma":0.0017360516,"threshold_uncertainty_score":0.99873036},"labels":[],"label_agreement":null},{"id":"W4402405754","doi":"10.23889/ijpds.v9i5.2744","title":"Using machine learning to gain insights into chronic disease multimorbidity: trends and patterns in British Columbia, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Multimorbidity; Disease; Artificial intelligence; Computer science; Data science; Medicine; Internal medicine","score_opus":0.07202401549061906,"score_gpt":0.39381359675455235,"score_spread":0.3217895812639333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405754","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99341315,0.000731294,0.002694573,0.0013214843,0.0013283294,0.00017508163,0.00028652206,0.000021930728,0.000027663826],"genre_scores_gemma":[0.997556,0.00010551084,0.00071436825,0.00015587987,0.00033652544,0.0000052755395,0.0007476713,0.000011458958,0.00036733705],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984278,0.000018652105,0.00027504715,0.00038517843,0.00070931367,0.00018402297],"domain_scores_gemma":[0.9993803,0.000035703444,0.000060562503,0.0001606247,0.0001097372,0.00025308877],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00035123483,0.00007200413,0.0001040519,0.00035115378,0.00020729388,0.0012413618,0.0003951988,0.000013280446,0.00013108249],"category_scores_gemma":[0.00031727,0.00009531293,0.000022392207,0.00036431997,0.00004898012,0.0011885813,0.0003019319,0.00015352234,6.88791e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000556994,0.000075023265,0.80307215,0.00020812519,0.00007817098,0.0013246208,0.0001584238,0.010179898,0.0004101344,0.00025479103,0.0017830421,0.18239991],"study_design_scores_gemma":[0.0004089964,0.000024598745,0.4686694,0.0004959594,0.0000261219,0.00006279008,0.000056235924,0.5198314,0.0000018148559,0.00016370596,0.0101714395,0.000087484295],"about_ca_topic_score_codex":0.72010756,"about_ca_topic_score_gemma":0.95409334,"teacher_disagreement_score":0.50965154,"about_ca_system_score_codex":0.0012810995,"about_ca_system_score_gemma":0.0010971478,"threshold_uncertainty_score":0.99979544},"labels":[],"label_agreement":null},{"id":"W4402405759","doi":"10.23889/ijpds.v9i5.2745","title":"Outcomes of the Health Data Research Network (HDRN) Canada and Canadian Longitudinal Study on Aging (CLSA) Partnership","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Frailty in Older Adults","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Quebec Statistical Institute; Nova Scotia Health Authority; Manitoba Health; Alberta Health Services; Canadian Institute for Health Information; University of Alberta","funders":"","keywords":"General partnership; Longitudinal data; Longitudinal study; Gerontology; Geography; Demography; Medicine; Business; Sociology","score_opus":0.47726291233236806,"score_gpt":0.5399349732759248,"score_spread":0.0626720609435567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405759","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8754044,0.00059395767,0.00031340192,0.113419525,0.00682101,0.0012358828,0.001916392,0.000019335708,0.00027607195],"genre_scores_gemma":[0.9982527,0.000016812688,0.0003274122,0.0004862437,0.00036652794,0.0000025191457,0.00024033328,0.000008182147,0.0002992843],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969677,0.00008170307,0.00036311036,0.00040155475,0.0018216547,0.00036429314],"domain_scores_gemma":[0.99808824,0.00034021787,0.000103538056,0.0008005985,0.0003902555,0.0002771235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049347943,0.000078892175,0.00013274027,0.00028975346,0.0005552644,0.00027395834,0.0018741613,0.000015513364,0.000015835103],"category_scores_gemma":[0.0018956322,0.000053397715,0.000016068192,0.0004985605,0.0001480043,0.0007302007,0.00059788045,0.0003463524,9.312617e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002169149,0.000025446781,0.95104647,0.000014002892,0.0000584428,0.000026334754,0.0001694526,0.00012540359,0.0000017759338,0.0012468989,0.040582493,0.006681575],"study_design_scores_gemma":[0.00027289992,0.00009822831,0.9725179,0.00029060998,0.000013380768,0.00012093013,0.00025243414,0.013475291,0.000001978072,0.00028107638,0.012625801,0.00004943525],"about_ca_topic_score_codex":0.8618329,"about_ca_topic_score_gemma":0.9862621,"teacher_disagreement_score":0.12442913,"about_ca_system_score_codex":0.00071169576,"about_ca_system_score_gemma":0.0041982406,"threshold_uncertainty_score":0.7447499},"labels":[],"label_agreement":null},{"id":"W4402405766","doi":"10.23889/ijpds.v9i5.2717","title":"Extracting Social Determinants of Health from Inpatient Electronic Medical Records","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"","keywords":"Health records; Medical record; Electronic health record; Data science; Computer science; Medicine; Health care; Political science; Internal medicine","score_opus":0.33987723630084865,"score_gpt":0.5995087051125427,"score_spread":0.2596314688116941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405766","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9544175,0.0005590872,0.01059487,0.012494399,0.01927309,0.0005743891,0.0017667285,0.00007482309,0.0002450589],"genre_scores_gemma":[0.99562186,0.00019829694,0.0015583163,0.00055164966,0.0013821505,0.000012826131,0.00059116125,0.0000124171,0.00007131011],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9961661,0.00020196087,0.0013028411,0.00036132906,0.0014866043,0.00048115692],"domain_scores_gemma":[0.9978413,0.0005549148,0.0007045869,0.00021995841,0.00050740835,0.00017186182],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005567847,0.00009808433,0.00021404953,0.00038719067,0.0017121864,0.00008559457,0.0013722401,0.00010871228,0.0005821093],"category_scores_gemma":[0.0020537472,0.00008988796,0.00005894794,0.00034053915,0.000112470625,0.0017138252,0.00037284245,0.0006944889,0.000027287671],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023699367,0.00023223751,0.35893327,0.00031447227,0.00011444608,0.000015464413,0.011150891,0.0000565789,0.000082644765,0.07579649,0.021326272,0.53174025],"study_design_scores_gemma":[0.0015755972,0.00031301478,0.49635667,0.0026910792,0.000046214205,0.000052561303,0.0032592926,0.25244206,0.000019891175,0.04272172,0.20011307,0.00040883897],"about_ca_topic_score_codex":0.0031571214,"about_ca_topic_score_gemma":0.0025367914,"teacher_disagreement_score":0.53133136,"about_ca_system_score_codex":0.0006687982,"about_ca_system_score_gemma":0.003292103,"threshold_uncertainty_score":0.9995875},"labels":[],"label_agreement":null},{"id":"W4402405772","doi":"10.23889/ijpds.v9i5.2746","title":"Understanding Patterns of Care for Older Adults: Data to Action","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Saskatchewan Health Quality Council","funders":"","keywords":"Action (physics); Computer science; Data science; Psychology","score_opus":0.6292349832746003,"score_gpt":0.5604133632468663,"score_spread":0.06882162002773395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405772","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30279794,0.00022079465,0.6487759,0.0136581855,0.023793878,0.002147348,0.007866313,0.0000943795,0.0006452984],"genre_scores_gemma":[0.9962203,0.000073139534,0.0019544917,0.0000743794,0.0007321937,0.000010206429,0.00085768383,0.000006907564,0.00007068574],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99804217,0.000027146712,0.00031827547,0.00040102281,0.0010149659,0.00019644546],"domain_scores_gemma":[0.99884826,0.0001402818,0.00011462618,0.00036371828,0.00042183453,0.00011130403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018946666,0.0000652958,0.000080407386,0.00022653569,0.00053713704,0.0005662683,0.002043798,0.000028154516,0.000057858084],"category_scores_gemma":[0.00093380356,0.00005975397,0.000040058185,0.00022430714,0.00009240974,0.0028054113,0.00030214468,0.000058335052,0.0000023804123],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006762972,0.0003412651,0.24985385,0.00088126573,0.00024749627,0.000005484453,0.059678264,0.0012106923,0.0008378363,0.2421052,0.034869663,0.4092927],"study_design_scores_gemma":[0.0027392136,0.00056656066,0.14978988,0.0045532803,0.00023104122,0.000021256257,0.19959691,0.0947332,0.0005296664,0.03131137,0.5147808,0.0011468045],"about_ca_topic_score_codex":0.0010379404,"about_ca_topic_score_gemma":0.0045016464,"teacher_disagreement_score":0.6934224,"about_ca_system_score_codex":0.00072392385,"about_ca_system_score_gemma":0.00026400218,"threshold_uncertainty_score":0.5460538},"labels":[],"label_agreement":null},{"id":"W4402405775","doi":"10.23889/ijpds.v9i5.2732","title":"Validation of the Passive Surveillance Stroke Severity score in three Canadian provinces","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Sunnybrook Health Science Centre; Hamilton Health Sciences; Dalhousie University; University Health Network; McMaster University Medical Centre; University of British Columbia","funders":"","keywords":"Stroke (engine); Medicine; Environmental health; Engineering","score_opus":0.04296074810974498,"score_gpt":0.3429649790054137,"score_spread":0.3000042308956687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405775","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98561496,0.000060467686,0.0023241753,0.00705258,0.0031058383,0.00040495646,0.0006657887,0.00001044757,0.00076080154],"genre_scores_gemma":[0.99825215,0.000012031208,0.0010482406,0.00010478241,0.00019894794,0.000005000726,0.00015678395,0.0000051295324,0.00021692803],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99855196,0.000013298888,0.00029598334,0.00023054166,0.0007611769,0.00014701785],"domain_scores_gemma":[0.9991737,0.000045217646,0.00013173149,0.00027903292,0.00029832136,0.000071982926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008773628,0.00006371154,0.00008896299,0.00034549428,0.00009628696,0.00014293153,0.0009497267,0.000023560164,0.000028124097],"category_scores_gemma":[0.0006984897,0.000044740867,0.00003857864,0.0003432947,0.00010747301,0.00088114763,0.00019363008,0.00014015882,0.0000019296363],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043524622,0.00002439905,0.9631024,0.000035188976,0.000053487714,0.000025594145,0.00008950053,0.00027936476,0.0019330366,0.0022444162,0.0054208147,0.026748264],"study_design_scores_gemma":[0.0002719524,0.00002208118,0.94961405,0.00022872309,0.000015041611,0.000111132125,0.00004879518,0.03905599,0.0010073198,0.00050214725,0.009059389,0.00006336266],"about_ca_topic_score_codex":0.010579399,"about_ca_topic_score_gemma":0.025685156,"teacher_disagreement_score":0.038776625,"about_ca_system_score_codex":0.0005461922,"about_ca_system_score_gemma":0.0007692987,"threshold_uncertainty_score":0.99600923},"labels":[],"label_agreement":null},{"id":"W4402405779","doi":"10.23889/ijpds.v9i5.2731","title":"Our Data, Our Truths, Our Voice: Reclaiming First Nations Data Sovereignty in Manitoba","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"First Nations Health and Social Secretariat of Manitoba","funders":"","keywords":"Sovereignty; Political science; Law; Politics","score_opus":0.1629812819286429,"score_gpt":0.4609647282512186,"score_spread":0.2979834463225757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405779","genre_codex":"editorial","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25198814,0.0039430023,0.059783403,0.24783608,0.31159484,0.008922171,0.056172345,0.0012000073,0.058560003],"genre_scores_gemma":[0.98018986,0.002528641,0.0056645162,0.000079532256,0.0052331127,0.000003520138,0.005220855,0.000020313963,0.0010596357],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99581003,0.00014461057,0.00073956186,0.00094084995,0.0017933055,0.00057163823],"domain_scores_gemma":[0.9972569,0.0002185867,0.00032029013,0.0013225873,0.00062861975,0.0002530417],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0076297694,0.00016273462,0.0001603881,0.0010198257,0.008034229,0.0020006646,0.008435684,0.000105902735,0.00002470306],"category_scores_gemma":[0.0008626156,0.00014628335,0.000037813323,0.0010872312,0.000070810325,0.011503843,0.00015432456,0.00038746223,0.00007836794],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009280069,0.00061248516,0.023894938,0.0001524904,0.00015141626,0.00008236327,0.039286632,0.0011455459,0.000023102866,0.860505,0.05417415,0.01987906],"study_design_scores_gemma":[0.00034403254,0.000023865277,0.007913943,0.00038807394,0.000034935336,0.000080901606,0.022236265,0.04901425,0.0000059602,0.010595603,0.90902424,0.00033792784],"about_ca_topic_score_codex":0.059469964,"about_ca_topic_score_gemma":0.78802073,"teacher_disagreement_score":0.8548501,"about_ca_system_score_codex":0.0010198477,"about_ca_system_score_gemma":0.0107801175,"threshold_uncertainty_score":0.99903536},"labels":[],"label_agreement":null},{"id":"W4402405796","doi":"10.23889/ijpds.v9i5.2754","title":"The Kids’ Environment and Health Cohort: a novel administrative data resource for research on the environmental determinants of child health in England","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Resource (disambiguation); Child health; Health data; Environmental health; Environmental research; Environmental data; Medicine; Environmental resource management; Psychology; Computer science; Environmental science; Pediatrics; Political science; Health care; Economic growth; Economics","score_opus":0.42627449205949086,"score_gpt":0.5245513289007545,"score_spread":0.09827683684126365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405796","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7591755,0.001379859,0.0014552396,0.22133407,0.0012597734,0.0035923123,0.011631878,0.000013609169,0.00015777908],"genre_scores_gemma":[0.9961584,0.0016698135,0.0005399226,0.00093747344,0.00018051505,0.000026951624,0.00042380605,0.000010232418,0.000052862466],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99757,0.000086130734,0.0004917181,0.00047680794,0.0009792013,0.00039615066],"domain_scores_gemma":[0.9983239,0.0007269915,0.00022808125,0.0005422251,0.000010229941,0.00016852697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011891755,0.000092422386,0.00011718937,0.000119862314,0.0010868892,0.0002653131,0.0017445621,0.000022693732,0.000034998207],"category_scores_gemma":[0.0003942114,0.000056332367,0.000017003744,0.00015838476,0.00049621746,0.00073093397,0.00087661005,0.00024637414,0.0000048469406],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007707732,0.0006703082,0.30159268,0.000100015815,0.00005568915,0.0000099134595,0.0059530153,0.0007553022,0.0005818285,0.0065391455,0.050431784,0.6325395],"study_design_scores_gemma":[0.0006083314,0.00059596245,0.6305853,0.0003871829,0.000004405644,0.00011420623,0.0006985015,0.09082997,0.000047908907,0.0013432361,0.27466047,0.00012452071],"about_ca_topic_score_codex":0.0003626998,"about_ca_topic_score_gemma":0.0012711575,"teacher_disagreement_score":0.632415,"about_ca_system_score_codex":0.0005857006,"about_ca_system_score_gemma":0.00012539259,"threshold_uncertainty_score":0.8359583},"labels":[],"label_agreement":null},{"id":"W4402405797","doi":"10.23889/ijpds.v9i5.2715","title":"Using linked data to inform multidimensional real-world issues: Canadian examples","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Computer science; Data science","score_opus":0.33289004148473256,"score_gpt":0.5023358135751167,"score_spread":0.16944577209038414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405797","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4676145,0.0016880827,0.07962246,0.18747166,0.16795716,0.008053124,0.030263962,0.0013027656,0.0560263],"genre_scores_gemma":[0.9414273,0.00014886276,0.05227177,0.0006284125,0.00217159,0.0000098161645,0.0013992959,0.000015972557,0.001927004],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966395,0.0000351265,0.00062128884,0.00041332163,0.0018384204,0.00045233124],"domain_scores_gemma":[0.9974424,0.00018225095,0.00017573877,0.0005724882,0.0012137792,0.00041331386],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0054120733,0.00012271684,0.00013291123,0.001715877,0.0023784891,0.00159238,0.0032861352,0.000045640725,0.0001282434],"category_scores_gemma":[0.00176084,0.00011368028,0.000039327348,0.0015191144,0.00023778333,0.007987068,0.00074714306,0.00015492753,0.00007011089],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000062026156,0.000048049882,0.08515373,0.000050463757,0.00034281265,0.000049387392,0.02703736,0.004814701,0.0005387448,0.7377435,0.09766924,0.046489995],"study_design_scores_gemma":[0.00011204472,0.000008961784,0.027185118,0.00015811944,0.000013749143,0.000022597804,0.001946995,0.048440926,0.0000030051444,0.00095251907,0.9209785,0.00017748552],"about_ca_topic_score_codex":0.41145948,"about_ca_topic_score_gemma":0.5745421,"teacher_disagreement_score":0.82330924,"about_ca_system_score_codex":0.00074498693,"about_ca_system_score_gemma":0.001647174,"threshold_uncertainty_score":0.99944407},"labels":[],"label_agreement":null},{"id":"W4402405798","doi":"10.23889/ijpds.v9i5.2587","title":"The employment, retention and exit of public school teachers in New Brunswick, Canada: an analysis using linked administrative data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Psychology; Business; Mathematics education; Demographic economics; Public administration; Political science; Economics","score_opus":0.6082030703870391,"score_gpt":0.5889861933433733,"score_spread":0.019216877043665814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405798","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.936767,0.00026428417,0.054057106,0.0063075577,0.0019110771,0.00024346609,0.00035531097,0.00000859671,0.00008560612],"genre_scores_gemma":[0.99518746,0.0000979099,0.003748459,0.00006643308,0.00016653788,7.4794235e-7,0.00039286262,0.0000039497136,0.00033566734],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955694,0.00016346546,0.0008757672,0.0005227489,0.0026899904,0.0001786355],"domain_scores_gemma":[0.99738896,0.00048275618,0.00043851117,0.00078192266,0.000709726,0.00019810685],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.013679689,0.00008537734,0.00013601487,0.0010650858,0.00036342477,0.0022397398,0.0032933864,0.00002637232,0.000112265145],"category_scores_gemma":[0.004659514,0.000056940153,0.000032498698,0.0020573058,0.00013598106,0.007328051,0.00045253188,0.00016390589,0.0000011670141],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041942272,0.00003649636,0.8748063,0.0000020754853,0.00017875084,0.000004679275,0.0003906744,0.0037693516,0.00028321848,0.014387618,0.0026333209,0.10346558],"study_design_scores_gemma":[0.000126961,0.000019158715,0.4214977,0.00001667879,0.000030355353,0.000011167576,0.00082249433,0.5693114,0.0000059210633,0.0016587904,0.0064490554,0.00005033226],"about_ca_topic_score_codex":0.10838022,"about_ca_topic_score_gemma":0.7990129,"teacher_disagreement_score":0.6906327,"about_ca_system_score_codex":0.00033456282,"about_ca_system_score_gemma":0.009873149,"threshold_uncertainty_score":0.99879605},"labels":[],"label_agreement":null},{"id":"W4402405837","doi":"10.23889/ijpds.v9i5.2584","title":"Wastewater-Based Surveillance of Substances of Potential Abuse","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Electrochemical Analysis and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Wastewater; Environmental science; Waste management; Business; Environmental engineering; Engineering","score_opus":0.026555241031714232,"score_gpt":0.34253958416367597,"score_spread":0.3159843431319617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405837","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98139995,0.0002292163,0.016963543,0.00037613715,0.00028542205,0.00002799151,0.0005911248,0.000014254384,0.00011235355],"genre_scores_gemma":[0.99665165,0.00005260131,0.0025958691,0.000007884248,0.00016388383,0.0000025406894,0.00044865362,0.000004738223,0.000072181305],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99869287,0.000004370002,0.00039253815,0.00021581721,0.00058883015,0.000105603],"domain_scores_gemma":[0.99910814,0.000071259456,0.00020386644,0.00024138145,0.00033201257,0.000043367105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041845994,0.00005818369,0.00009857626,0.0001367479,0.00007101734,0.00010819543,0.0011531985,0.00002237573,0.00009422378],"category_scores_gemma":[0.000092224,0.000046949444,0.00007054255,0.00026443874,0.00012060521,0.00051224546,0.000049266066,0.00007334563,0.0000015323375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030370462,0.00005075766,0.003691379,0.000038889186,0.00004249466,0.0000011671129,0.00002370311,0.00141015,0.9874285,0.0028856653,0.00020687951,0.0041900617],"study_design_scores_gemma":[0.00032887293,0.000019866673,0.0019246419,0.00020189516,0.000037493013,0.000027123548,0.000044018347,0.3540959,0.6322399,0.0036814369,0.007249795,0.00014909227],"about_ca_topic_score_codex":0.000032132317,"about_ca_topic_score_gemma":0.000017895776,"teacher_disagreement_score":0.3551886,"about_ca_system_score_codex":0.000043636588,"about_ca_system_score_gemma":0.00009569179,"threshold_uncertainty_score":0.21429491},"labels":[],"label_agreement":null},{"id":"W4402405858","doi":"10.23889/ijpds.v9i5.2839","title":"Urban Trail Exposure in Winnipeg, Canada: Longitudinal Cohort Development for a 20-Year Difference-in-Differences Analysis of a Natural Experiment with Varied Duration of Exposure Times","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Children's Hospital Research Institute of Manitoba; Manitoba Health","funders":"","keywords":"Duration (music); Environmental science; Cohort; Natural (archaeology); Geography; Statistics; Mathematics; Archaeology","score_opus":0.05668539627798016,"score_gpt":0.34440611574618235,"score_spread":0.2877207194682022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405858","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9926668,0.000108700944,0.005606559,0.000603892,0.0004021705,0.00034052416,0.00023700795,0.0000049279256,0.00002942744],"genre_scores_gemma":[0.99262404,0.00000969545,0.0068878117,0.000044692213,0.000033930603,0.000022847316,0.00027880573,0.0000046865134,0.00009348283],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99749464,0.000034447814,0.00075195223,0.00037756396,0.0011102303,0.00023114268],"domain_scores_gemma":[0.9991837,0.00014112981,0.00029983046,0.00018037032,0.000104803425,0.00009016764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001282763,0.00011660818,0.0002488784,0.00039930423,0.000117748314,0.00009222221,0.0007140466,0.000033878347,0.00010252896],"category_scores_gemma":[0.00019536687,0.00008970868,0.000035720725,0.0007884837,0.00013744753,0.00091881125,0.000100019635,0.000112883085,3.1350348e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020611766,0.00007838109,0.9908349,0.000024271158,0.00010229941,0.000003854552,0.0011973807,0.0022984599,0.00061394705,0.00094805873,0.00037420695,0.0033181326],"study_design_scores_gemma":[0.00037175257,0.00010205849,0.94559133,0.00012448359,0.00003993672,0.0000053136737,0.00024578776,0.052663755,0.00034228948,0.00012094005,0.00028820324,0.0001041444],"about_ca_topic_score_codex":0.027909916,"about_ca_topic_score_gemma":0.2932404,"teacher_disagreement_score":0.26533046,"about_ca_system_score_codex":0.0006724079,"about_ca_system_score_gemma":0.0007003502,"threshold_uncertainty_score":0.9785633},"labels":[],"label_agreement":null},{"id":"W4402405865","doi":"10.23889/ijpds.v9i5.2853","title":"Development of International Classification of Diseases crosswalks using text analysis methods.","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Persona Design and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Data mining; Data science","score_opus":0.1984340021382891,"score_gpt":0.4982774218041409,"score_spread":0.2998434196658518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405865","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032259,0.00014162702,0.96537465,0.00041093025,0.0013930714,0.00009728424,0.00022768723,0.000028451974,0.00006732822],"genre_scores_gemma":[0.53752524,0.0000127812245,0.46219626,0.000013667796,0.000071169095,0.0000041583266,0.0001460467,0.0000031408608,0.000027541153],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99778426,0.000032250013,0.00067340204,0.00042873443,0.00094381394,0.00013755128],"domain_scores_gemma":[0.9980955,0.0001537389,0.00039802317,0.00046546175,0.0007992569,0.00008801871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015682547,0.000091694594,0.00014560793,0.0010966859,0.00021635549,0.00055766635,0.0036308519,0.000028517285,0.000019095103],"category_scores_gemma":[0.00031486485,0.00008281867,0.00010631519,0.0014504032,0.00013379642,0.0029489687,0.00044336857,0.00007711034,0.000002143912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033180404,0.0002509043,0.0139692575,0.00003272178,0.00089961,0.0000029843509,0.0012648351,0.0038716241,0.23516884,0.2400418,0.00043838588,0.5040258],"study_design_scores_gemma":[0.000103019294,0.000006160105,0.06560764,0.000042255135,0.00006737107,0.00001633305,0.00005259714,0.92190516,0.002395141,0.0020923424,0.007615435,0.000096531716],"about_ca_topic_score_codex":0.00002694824,"about_ca_topic_score_gemma":0.000007762564,"teacher_disagreement_score":0.91803354,"about_ca_system_score_codex":0.00019256503,"about_ca_system_score_gemma":0.00053550256,"threshold_uncertainty_score":0.67470866},"labels":[],"label_agreement":null},{"id":"W4402405872","doi":"10.23889/ijpds.v9i5.2542","title":"Are Métis mothers receiving adequate prenatal care in Ontario? A population-based study","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Breastfeeding Practices and Influences","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Métis National Council","funders":"","keywords":"Prenatal care; Medicine; Population; Environmental health; Pediatrics","score_opus":0.07481489378111676,"score_gpt":0.402770840417935,"score_spread":0.3279559466368182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405872","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9926667,0.00014978145,0.00058310776,0.0028033769,0.0031712516,0.00039095525,0.00010092436,0.000036935307,0.000096954],"genre_scores_gemma":[0.99731266,0.0000028658997,0.0018355537,0.00015665001,0.00025577494,0.0000135136,0.00024012108,0.000012645491,0.0001702399],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99786484,0.000027416265,0.00043880005,0.00043938085,0.0010079313,0.00022161614],"domain_scores_gemma":[0.9988668,0.000120982964,0.0002730668,0.00026384465,0.00036670506,0.00010861791],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001183502,0.000114074515,0.00014022397,0.0006031629,0.0002167848,0.0006870922,0.0007063894,0.000036474677,0.0001717174],"category_scores_gemma":[0.00068515335,0.00009579124,0.000049863458,0.0003676641,0.00003673484,0.0032171544,0.00012038588,0.00032280988,0.000007507507],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014869601,0.00007848485,0.9756092,0.000022149592,0.000035517955,0.000066904126,0.0009331288,0.0013077887,0.00002008192,0.00016811359,0.00006948373,0.021540446],"study_design_scores_gemma":[0.00064396806,0.00012677698,0.9707925,0.00066370773,0.000038293972,0.00011748847,0.0010493329,0.025118148,0.000006682051,0.00010117351,0.0012378973,0.00010403484],"about_ca_topic_score_codex":0.03214997,"about_ca_topic_score_gemma":0.05417339,"teacher_disagreement_score":0.023810359,"about_ca_system_score_codex":0.0008284799,"about_ca_system_score_gemma":0.00044743036,"threshold_uncertainty_score":0.974295},"labels":[],"label_agreement":null},{"id":"W4402405898","doi":"10.23889/ijpds.v9i5.2803","title":"Using Administrative Data to Identify Factors Associated with Healthy Development After Experiencing Household Challenge Adversity in Early Childhood","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; First Nations Health and Social Secretariat of Manitoba; Manitoba Health","funders":"","keywords":"Early childhood; Psychology; Developmental psychology; Environmental health; Medicine","score_opus":0.3628899781143234,"score_gpt":0.4844615259743103,"score_spread":0.12157154785998692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405898","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99306846,0.00007140558,0.0024540713,0.0013125738,0.0023281272,0.0003417915,0.0002958605,0.000043341686,0.00008439699],"genre_scores_gemma":[0.9938119,0.00001909092,0.005392188,0.00017772046,0.00024063283,0.0000073719684,0.00028638836,0.00001118435,0.000053519678],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99710083,0.00007142434,0.00042670322,0.00060052314,0.0014354859,0.00036503663],"domain_scores_gemma":[0.9988349,0.00012446086,0.0001611377,0.00030593385,0.00029155693,0.00028197307],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0024736747,0.00012918565,0.000121624755,0.00056873966,0.00079664757,0.0010814026,0.0020040588,0.000048971586,0.000044905973],"category_scores_gemma":[0.00092249626,0.00011655136,0.000019966688,0.0007670351,0.000110114255,0.004771706,0.000435441,0.00020170286,0.000004456749],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013638458,0.0005036511,0.5312842,0.000012705477,0.00018778603,0.000058625137,0.44806552,0.00054846145,0.00005959254,0.0026581276,0.00076376717,0.01572117],"study_design_scores_gemma":[0.00021276489,0.000036137168,0.98476213,0.00029781155,0.0000065639447,0.0000038978287,0.008237511,0.00036496387,0.000013811393,0.00011774487,0.0057509826,0.00019569753],"about_ca_topic_score_codex":0.00090419577,"about_ca_topic_score_gemma":0.0067981696,"teacher_disagreement_score":0.45347792,"about_ca_system_score_codex":0.0011999807,"about_ca_system_score_gemma":0.0037249487,"threshold_uncertainty_score":0.9999556},"labels":[],"label_agreement":null},{"id":"W4402405902","doi":"10.23889/ijpds.v9i5.2816","title":"Uncharted territory in linking population-based laboratory data for the epidemiology of celiac disease in Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Celiac Disease Research and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"","keywords":"Epidemiology; Disease; Population; Environmental health; Medicine; Geography; Pathology","score_opus":0.11004934780871602,"score_gpt":0.44145994676556605,"score_spread":0.33141059895685004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405902","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7766321,0.01304576,0.076084435,0.083127484,0.015305132,0.004843571,0.030868318,0.00005849266,0.00003473139],"genre_scores_gemma":[0.9933074,0.00011705134,0.0010479423,0.00044310212,0.00030101513,0.000023986135,0.00473304,0.000007986153,0.000018489163],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99817085,0.00005270839,0.0005232664,0.00035107785,0.00067252584,0.00022958222],"domain_scores_gemma":[0.99805164,0.00083561416,0.00012807641,0.00057580025,0.0002536647,0.00015517749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00310384,0.00007471113,0.00014046367,0.00042919052,0.00008860068,0.000048923823,0.0012209143,0.00001627962,0.000020672169],"category_scores_gemma":[0.003621962,0.000055369306,0.000031309024,0.00034072073,0.000061251565,0.00074233126,0.0002549323,0.00014750999,4.7791406e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003191896,0.000060100363,0.9675871,0.0001562546,0.00003984184,0.000039766,0.000012134137,0.009087392,0.000059469417,0.0019999377,0.004201818,0.01643699],"study_design_scores_gemma":[0.00036557546,0.0000108221375,0.4920912,0.00026198392,0.000017569602,0.0000012642373,0.00002643262,0.4947438,0.0000026129346,0.00048390677,0.011956919,0.000037904672],"about_ca_topic_score_codex":0.19528262,"about_ca_topic_score_gemma":0.28791836,"teacher_disagreement_score":0.4856564,"about_ca_system_score_codex":0.00073859555,"about_ca_system_score_gemma":0.0036455258,"threshold_uncertainty_score":0.81007606},"labels":[],"label_agreement":null},{"id":"W4402405923","doi":"10.23889/ijpds.v9i5.2796","title":"Inequalities in Ambulatory Care Sensitive Conditions: An International Comparison of High-Income Countries","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Inequality; Ambulatory; Primary care; Economics; Demographic economics; Medicine; Environmental health; Internal medicine; Mathematics; Family medicine","score_opus":0.14921828481286417,"score_gpt":0.5755514295207518,"score_spread":0.42633314470788763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405923","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9728646,0.00038564444,0.001590479,0.0020137287,0.016978323,0.00048972864,0.005308483,0.00006900765,0.00029997755],"genre_scores_gemma":[0.99390066,0.000092364055,0.0025369627,0.00031849515,0.0008934871,0.00002000349,0.0021419812,0.000014975094,0.000081052036],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99660337,0.00016567254,0.0011710204,0.00042381944,0.0013076836,0.00032843312],"domain_scores_gemma":[0.9961377,0.00074296544,0.00043840447,0.00035353974,0.0021905452,0.00013684935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019658972,0.00013583689,0.00025202858,0.00075516215,0.00049437705,0.0001724381,0.001398262,0.00009651622,0.00013577662],"category_scores_gemma":[0.0010824004,0.00012840638,0.000047915866,0.0003435618,0.00024281538,0.00432855,0.0003524778,0.00042154212,0.00003815663],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034047477,0.0000999125,0.6648624,0.00047455097,0.000103287326,0.000035920842,0.022495475,0.0027211353,0.00023203723,0.29985616,0.005863231,0.0029154364],"study_design_scores_gemma":[0.0011654333,0.00017718766,0.8570809,0.0030380797,0.000030484538,0.00004094771,0.02706312,0.056339778,0.00017337389,0.007406909,0.047158934,0.00032487037],"about_ca_topic_score_codex":0.0023187448,"about_ca_topic_score_gemma":0.0019193192,"teacher_disagreement_score":0.29244927,"about_ca_system_score_codex":0.0011159418,"about_ca_system_score_gemma":0.0009074324,"threshold_uncertainty_score":0.523626},"labels":[],"label_agreement":null},{"id":"W4402405953","doi":"10.23889/ijpds.v9i5.2814","title":"Expanding opportunities in health data: Enhancing research by facilitating linkage of Ontario’s population-level health administrative data with data from patient support programs (PSPs)","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Linkage (software); Health data; Population health; Population; Data science; Computer science; Business; Medicine; Knowledge management; Environmental health; Health care; Political science; Genetics; Biology","score_opus":0.692027672097651,"score_gpt":0.6150439469396842,"score_spread":0.07698372515796681,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402405953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5180672,0.0036038442,0.07020602,0.06682382,0.014416192,0.007916061,0.31789175,0.00024940268,0.000825724],"genre_scores_gemma":[0.7215121,0.00040137244,0.03939039,0.0015829708,0.0005020218,0.000043644577,0.23587987,0.000037785892,0.00064987346],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9920781,0.0006268588,0.0024753565,0.0013813606,0.0025385942,0.00089968403],"domain_scores_gemma":[0.9933757,0.0016718807,0.001182469,0.0025992566,0.0007578204,0.0004128792],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.018254321,0.00022507386,0.000488031,0.000728984,0.0015504949,0.00038105054,0.006237984,0.00008955957,0.00018812797],"category_scores_gemma":[0.00197253,0.0001899153,0.000022521604,0.0006166981,0.00020281548,0.008916197,0.0042204787,0.001276193,0.000008114265],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006636579,0.0005368593,0.38055795,0.0015171571,0.000285477,0.00009414307,0.03877583,0.00008935972,0.00011505863,0.0032058363,0.1923247,0.38183397],"study_design_scores_gemma":[0.0040240297,0.0025088792,0.20585601,0.013878743,0.00007418102,0.00012687183,0.074450515,0.07835451,0.000020843321,0.0045349197,0.6148309,0.0013396138],"about_ca_topic_score_codex":0.22553743,"about_ca_topic_score_gemma":0.3734028,"teacher_disagreement_score":0.42250618,"about_ca_system_score_codex":0.0035266562,"about_ca_system_score_gemma":0.026608791,"threshold_uncertainty_score":0.99974936},"labels":[],"label_agreement":null},{"id":"W4402406008","doi":"10.23889/ijpds.v9i5.2800","title":"Transparent reporting on multi-site studies about algorithms for linked health data: A systematic review of Health Data Research Network Canada’s Algorithms Inventory","year":2024,"lang":"en","type":"review","venue":"International Journal for Population Data Science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Algorithm; Computer science; Data mining; Health data; Data science; Health care; Political science","score_opus":0.9185031121271087,"score_gpt":0.7259421849331035,"score_spread":0.1925609271940052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406008","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.873931e-7,0.93038356,0.007915179,0.0059024314,0.015454022,0.010904206,0.029395983,0.00004066321,0.0000032762441],"genre_scores_gemma":[0.000015486949,0.95596653,0.009744631,0.0013284252,0.002420909,0.0005506295,0.029664006,0.0000912508,0.00021814664],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.97328216,0.0032854094,0.014932263,0.0022578298,0.0045379517,0.0017043947],"domain_scores_gemma":[0.9678751,0.0041681486,0.017401744,0.004900001,0.0050672665,0.0005877097],"candidate_categories":["metaresearch","metaepi_narrow","sts","open_science","research_integrity"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.11623327,0.0005519785,0.0038460935,0.00086204224,0.0036054433,0.00018327648,0.010841693,0.00021244271,0.0000126806435],"category_scores_gemma":[0.04892088,0.0004110843,0.00024188885,0.0013766926,0.0003029389,0.0015267537,0.0037244626,0.0023833762,0.00001671459],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.000012932245,0.000058308873,0.00007795332,0.7871302,0.00036180916,0.000013107416,0.00045295735,0.000038142116,1.3551103e-8,0.00041012914,0.072873674,0.1385708],"study_design_scores_gemma":[0.000093944895,0.00009730697,0.000013097834,0.67996466,0.00030589476,0.000043098786,0.0007117102,0.04652381,1.0572499e-8,0.00014185155,0.2718677,0.00023694143],"about_ca_topic_score_codex":0.15389869,"about_ca_topic_score_gemma":0.37456226,"teacher_disagreement_score":0.22066358,"about_ca_system_score_codex":0.0060510053,"about_ca_system_score_gemma":0.039422836,"threshold_uncertainty_score":0.99991816},"labels":[{"model":"gemma","categories":["metaresearch"],"domain":"reporting","study_design":"systematic_review","genre":"review","about_ca_system":true,"about_ca_topic":true,"confidence":"low"},{"model":"gpt","categories":["metaresearch"],"domain":"reporting","study_design":"systematic_review","genre":"review","about_ca_system":false,"about_ca_topic":true,"confidence":"low"}],"label_agreement":"agree"},{"id":"W4402406101","doi":"10.23889/ijpds.v9i5.2670","title":"Tailored Strategies for Mental Health Support: Distinctions-Based Approaches for the Red River Métis Community","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mental health; Psychology; Computer science; Data science; Psychiatry","score_opus":0.16962349184221062,"score_gpt":0.4297653928822379,"score_spread":0.2601419010400273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406101","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.122916736,0.00037180918,0.7095758,0.14350677,0.010075126,0.0032933783,0.009999932,0.000119433505,0.00014102484],"genre_scores_gemma":[0.9864494,0.000026164658,0.008700192,0.0010228488,0.0005707679,0.00004607462,0.0029848989,0.00001043907,0.00018919371],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985841,0.000032890348,0.0003861472,0.00022142875,0.0005191136,0.00025632276],"domain_scores_gemma":[0.9989103,0.00022027722,0.0001660871,0.00027561822,0.0002961422,0.00013156397],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0020414602,0.00009976435,0.0001275318,0.0001463677,0.0013844261,0.0004552636,0.0008073155,0.000025515548,0.00003002246],"category_scores_gemma":[0.00024223796,0.00006557837,0.0000907995,0.00014923901,0.00018668878,0.00092931,0.00010791576,0.00019191061,0.0000027634696],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005459755,0.0013053712,0.03404778,0.00153844,0.00076174433,0.00001160157,0.0035724973,0.0054839724,0.0009754036,0.3956144,0.33530864,0.21592042],"study_design_scores_gemma":[0.0029886914,0.0011373581,0.14609279,0.00045809246,0.000111697474,0.0004501087,0.0017656137,0.5513752,0.00006903314,0.035980504,0.25933373,0.00023714457],"about_ca_topic_score_codex":0.0005202212,"about_ca_topic_score_gemma":0.00021968759,"teacher_disagreement_score":0.86353266,"about_ca_system_score_codex":0.00030058293,"about_ca_system_score_gemma":0.0006654875,"threshold_uncertainty_score":0.99991566},"labels":[],"label_agreement":null},{"id":"W4402406104","doi":"10.23889/ijpds.v9i5.2659","title":"Understanding health data social licence: An international comparison of community attitudes towards health data use across Canada and Australia","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"The Quebec Population Health Research Network","funders":"","keywords":"Health data; Community health; Environmental health; Data science; Psychology; Computer science; Economic growth; Medicine; Health care; Economics","score_opus":0.8174414550539787,"score_gpt":0.5755350149044016,"score_spread":0.24190644014957707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.63408375,0.0006401059,0.13918073,0.088382,0.014201102,0.00070584903,0.12266954,0.00005976841,0.00007715528],"genre_scores_gemma":[0.9890833,0.00022914963,0.0026999316,0.00071157067,0.00033514865,0.000001353943,0.0068967734,0.0000087459675,0.000034013232],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99785966,0.00006267061,0.00096199394,0.00045008873,0.00036164792,0.00030393508],"domain_scores_gemma":[0.998109,0.0000994801,0.0006270952,0.0008677554,0.00011263783,0.00018407211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059664994,0.00010464719,0.00024693192,0.00019445915,0.0008614669,0.0009964817,0.00422548,0.000030857664,0.00002595464],"category_scores_gemma":[0.00057836383,0.00011495873,0.000016466067,0.00022808438,0.00015414768,0.0063445442,0.0019254358,0.0003098716,0.0000013973553],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006854164,0.0003093881,0.37812167,0.000285951,0.00027618892,0.000004351952,0.0068279468,0.0004426501,0.000004399737,0.5042088,0.057330016,0.05212009],"study_design_scores_gemma":[0.00042739863,0.00010455729,0.71806955,0.00016882589,0.0000056879526,0.000028840292,0.0022815766,0.15536673,0.0000012826567,0.004501775,0.11880284,0.00024091692],"about_ca_topic_score_codex":0.790578,"about_ca_topic_score_gemma":0.71438754,"teacher_disagreement_score":0.499707,"about_ca_system_score_codex":0.0010723255,"about_ca_system_score_gemma":0.00067619927,"threshold_uncertainty_score":0.96090966},"labels":[],"label_agreement":null},{"id":"W4402406113","doi":"10.23889/ijpds.v9i5.2668","title":"Exploring Disparities in Opioid Utilization: An Analysis Comparing Red River Métis to All Other Manitobans","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"","keywords":"Opioid; Environmental science; Medicine; Internal medicine","score_opus":0.34150269846386627,"score_gpt":0.44735829723148457,"score_spread":0.1058555987676183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406113","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9721793,0.00012822587,0.023056343,0.0022055565,0.0017770183,0.0002882033,0.00020791458,0.00005153478,0.00010593651],"genre_scores_gemma":[0.99154943,0.00009431811,0.0067287176,0.00024913438,0.00026325448,0.000026522424,0.000993686,0.000014137919,0.000080790196],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99818206,0.000019298377,0.00037945888,0.00042752665,0.0007656741,0.00022597695],"domain_scores_gemma":[0.9991678,0.00004475029,0.00006443355,0.00034156564,0.00022614667,0.00015529439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005936617,0.00011028105,0.00016942136,0.0012481547,0.00013007286,0.00047293623,0.00064948475,0.000019839123,0.000049570543],"category_scores_gemma":[0.00019547134,0.00009933919,0.000060699454,0.0008601563,0.000047103655,0.0030248153,0.00017525633,0.0001050271,0.0000104766395],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012928659,0.00020252513,0.9659104,0.000023689796,0.00034232,0.000052600753,0.0018615184,0.009687033,0.00036911256,0.008444883,0.00030833183,0.012668352],"study_design_scores_gemma":[0.00034450655,0.000054876666,0.79779875,0.0001875823,0.0001558602,0.00003360864,0.00029177443,0.19610307,0.00008604541,0.0003895116,0.0044512264,0.00010319677],"about_ca_topic_score_codex":0.0018831819,"about_ca_topic_score_gemma":0.0013591929,"teacher_disagreement_score":0.18641603,"about_ca_system_score_codex":0.0004241369,"about_ca_system_score_gemma":0.000103259204,"threshold_uncertainty_score":0.4560535},"labels":[],"label_agreement":null},{"id":"W4402406114","doi":"10.23889/ijpds.v9i5.2682","title":"Combining cohorts of prospectively collected and linked data to improve health after release from prison","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Global Health Research","funders":"","keywords":"Prison; Psychology; Medicine; Environmental science; Criminology","score_opus":0.12522520354951905,"score_gpt":0.5018545273271544,"score_spread":0.37662932377763536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406114","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98094505,0.00040487663,0.007118379,0.0020895207,0.003829706,0.00073361414,0.004808701,0.000033963945,0.00003617868],"genre_scores_gemma":[0.9936609,0.0000895199,0.0046286345,0.00015060348,0.0004911011,0.000025577458,0.00083361624,0.000012163804,0.00010788209],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979862,0.000087353714,0.00060926896,0.0004651901,0.0006237789,0.00022819283],"domain_scores_gemma":[0.9982977,0.00028547397,0.000291609,0.00038484042,0.0005558762,0.00018453009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018371397,0.00008567,0.00023550012,0.000241852,0.00056018564,0.00018716387,0.0010421027,0.000049388273,0.00004961328],"category_scores_gemma":[0.0012550083,0.0000736088,0.000016639375,0.0003498119,0.0000745306,0.0015656177,0.0008079364,0.0002633983,0.000005469005],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009423677,0.00021730422,0.8119708,0.0003046372,0.00024242236,0.000041415282,0.042150974,0.000043496293,0.003126515,0.013459089,0.0038892974,0.12361169],"study_design_scores_gemma":[0.00059432787,0.00011338035,0.94531786,0.0009701595,0.000021030395,0.0000018442857,0.0031451026,0.039455015,0.00002581111,0.003636812,0.00657202,0.00014661296],"about_ca_topic_score_codex":0.0038608306,"about_ca_topic_score_gemma":0.0030177664,"teacher_disagreement_score":0.1333471,"about_ca_system_score_codex":0.00024140374,"about_ca_system_score_gemma":0.00079271395,"threshold_uncertainty_score":0.5836446},"labels":[],"label_agreement":null},{"id":"W4402406122","doi":"10.23889/ijpds.v9i5.2676","title":"Exploring vaccine hesitancy among citizens of the Métis Nation of Ontario: a population-based data linkage study ","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; University of Toronto; University of Waterloo; University of Alberta; Métis National Council","funders":"","keywords":"Linkage (software); Population; Geography; Environmental health; Genetics; Medicine; Biology; Gene","score_opus":0.20197537485931757,"score_gpt":0.4012224652426426,"score_spread":0.19924709038332503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406122","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901553,0.00007087081,0.0033322177,0.0013317297,0.0041587246,0.00045709437,0.00033647273,0.00002468893,0.00013289653],"genre_scores_gemma":[0.9979576,0.000022900427,0.0010413972,0.000028033426,0.00045955137,0.000007872558,0.00026476826,0.000009907459,0.00020800569],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99697256,0.00009238402,0.00068806874,0.0004104396,0.0016235737,0.00021299765],"domain_scores_gemma":[0.99782234,0.00025213146,0.00042840574,0.0007218054,0.0007007718,0.000074513795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033700461,0.00010389654,0.00016064182,0.00040703575,0.00067608507,0.00037903804,0.0033658608,0.000033490887,0.000114643095],"category_scores_gemma":[0.0016942702,0.00008288397,0.00007064478,0.0007624438,0.000036909034,0.0055486006,0.00046081858,0.0001835129,0.0000014439006],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027541786,0.00010281357,0.9851743,0.000014207649,0.00004486535,0.00000434997,0.0025946489,0.0006478901,0.00011533557,0.005829856,0.0003698968,0.005074302],"study_design_scores_gemma":[0.00036386502,0.000042026615,0.98490316,0.00024286288,0.000051171974,0.000003077606,0.0005678644,0.010363794,0.000053054806,0.0015642107,0.0017437342,0.00010118155],"about_ca_topic_score_codex":0.054685134,"about_ca_topic_score_gemma":0.15902956,"teacher_disagreement_score":0.10434442,"about_ca_system_score_codex":0.0005359866,"about_ca_system_score_gemma":0.0011539155,"threshold_uncertainty_score":0.9516098},"labels":[],"label_agreement":null},{"id":"W4402406124","doi":"10.23889/ijpds.v9i5.2677","title":"Cardiovascular disease surveillance using electronic medical records: a scoping study","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; Libin Cardiovascular Institute of Alberta; University of Calgary","funders":"","keywords":"Medical record; Disease; Health records; Medicine; Electronic medical record; Environmental health; Business; Medical emergency; Computer science; Data science; Internal medicine; Political science; Health care","score_opus":0.3164783667786538,"score_gpt":0.5857902917225579,"score_spread":0.2693119249439041,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406124","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90637374,0.0026036405,0.063907854,0.0026636687,0.022195354,0.0017918022,0.00026861712,0.00014097041,0.00005438745],"genre_scores_gemma":[0.99628884,0.00026768996,0.0005348828,0.00020791365,0.0024637133,0.000040557512,0.00011093829,0.00002341353,0.000062082894],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9949125,0.0003642041,0.0009409282,0.0006704372,0.0025027674,0.0006091298],"domain_scores_gemma":[0.9971919,0.00059183914,0.00019366153,0.00067304855,0.00096837385,0.00038114167],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01037501,0.0001333219,0.0002062971,0.0004183224,0.0015046906,0.00026905263,0.0020967983,0.00006729698,0.0002808372],"category_scores_gemma":[0.0062252064,0.000116604824,0.000109181965,0.0005761036,0.00011707123,0.0020540738,0.00055698096,0.0007237383,0.000054357297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023087644,0.00015046883,0.8970787,0.00027919485,0.00040678505,0.00022315248,0.0014351475,0.0058680875,0.000042229527,0.008328731,0.00095533003,0.0850013],"study_design_scores_gemma":[0.0002795082,0.00007910498,0.030374419,0.0026817017,0.000057636258,0.000066378554,0.0014393736,0.9466348,0.000002968325,0.004833347,0.013281973,0.00026878656],"about_ca_topic_score_codex":0.0030575984,"about_ca_topic_score_gemma":0.0026377721,"teacher_disagreement_score":0.9407667,"about_ca_system_score_codex":0.0010366249,"about_ca_system_score_gemma":0.004584125,"threshold_uncertainty_score":0.9997952},"labels":[],"label_agreement":null},{"id":"W4402406136","doi":"10.23889/ijpds.v9i5.2657","title":"Navigating Data Acquisition and Data Quality Validation of Large Databases: Practical Lessons","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Saskatchewan Health Quality Council","funders":"","keywords":"Database; Computer science; Data quality; Quality (philosophy); Data mining; Data science; Engineering; Operations management","score_opus":0.6281295486631037,"score_gpt":0.6648589747416125,"score_spread":0.03672942607850882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406136","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06595144,0.00020447468,0.8357032,0.026695363,0.0046011815,0.00034389028,0.066365734,0.000045778826,0.000088934175],"genre_scores_gemma":[0.9157238,0.00012906549,0.046847533,0.00032763023,0.00050738733,0.0000025396942,0.036396317,0.000009690515,0.00005601757],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99327433,0.00027861583,0.0013223359,0.0013267556,0.0035490047,0.00024896918],"domain_scores_gemma":[0.9926621,0.0021004286,0.00074926333,0.003532158,0.00080841803,0.00014765745],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["metaresearch","scholarly_communication","open_science"],"category_scores_codex":[0.042797815,0.00012406052,0.00020190568,0.00028150933,0.00046708243,0.0026661928,0.008188024,0.00003369242,0.00014056846],"category_scores_gemma":[0.0253353,0.00010044949,0.000028326984,0.00072410493,0.00024186455,0.0271492,0.009238501,0.0002703435,0.000023142711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018760686,0.0003826917,0.010370395,0.0001014918,0.00018126826,0.000034779747,0.00058945373,0.00021222522,0.002072671,0.57250696,0.08859328,0.3247672],"study_design_scores_gemma":[0.00075492397,0.00005223366,0.02958228,0.0004835178,0.00011345001,0.0002233075,0.0021858478,0.63481325,0.0003244031,0.04551482,0.2855817,0.00037029432],"about_ca_topic_score_codex":0.0002974666,"about_ca_topic_score_gemma":0.00016895811,"teacher_disagreement_score":0.8497724,"about_ca_system_score_codex":0.00006888637,"about_ca_system_score_gemma":0.0002979884,"threshold_uncertainty_score":0.9987746},"labels":[],"label_agreement":null},{"id":"W4402406137","doi":"10.23889/ijpds.v9i5.2666","title":"Conceptualizing community data governance for race-related, population data: a scoping review and key informant interviews","year":2024,"lang":"en","type":"review","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Sunnybrook Health Science Centre; SickKids Foundation","funders":"","keywords":"Race (biology); Key (lock); Population; Corporate governance; Psychology; Business; Computer science; Sociology; Demography; Computer security; Finance; Gender studies","score_opus":0.6948268504810855,"score_gpt":0.6210748162597212,"score_spread":0.07375203422136434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406137","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000003482291,0.94066906,0.019812629,0.0011673731,0.0057906792,0.002736569,0.029702222,0.000042718137,0.00007528925],"genre_scores_gemma":[0.000048112917,0.9463527,0.0058294083,0.0006347199,0.00040862482,0.000054098884,0.046274595,0.00003394962,0.00036375367],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99015117,0.00064416864,0.0041891383,0.0016873744,0.002865253,0.00046288437],"domain_scores_gemma":[0.9865565,0.0020552923,0.0040274765,0.00625238,0.00086643186,0.00024192271],"candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["metaresearch","scholarly_communication","open_science"],"category_scores_codex":[0.045808423,0.00048478998,0.0015868772,0.0006573362,0.0011340831,0.004514263,0.027089179,0.00014664467,0.000083906525],"category_scores_gemma":[0.025646726,0.00035195638,0.00020933371,0.001161882,0.00033950096,0.018755615,0.019898457,0.0008691522,0.00006495248],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009488855,0.000035734487,0.000011821238,0.009915493,0.00014964918,0.0000028372654,0.00012362603,0.000008519429,5.250445e-8,0.010117696,0.061113525,0.91851157],"study_design_scores_gemma":[0.00025134574,0.000033301654,0.00003702739,0.093192734,0.0008997636,0.00015349727,0.00013339576,0.01245612,2.0955271e-8,0.0033869324,0.8890781,0.00037776656],"about_ca_topic_score_codex":0.00052288536,"about_ca_topic_score_gemma":0.0010836427,"teacher_disagreement_score":0.9181338,"about_ca_system_score_codex":0.00034650546,"about_ca_system_score_gemma":0.0006487189,"threshold_uncertainty_score":0.99989325},"labels":[],"label_agreement":null},{"id":"W4402406143","doi":"10.23889/ijpds.v9i5.2664","title":"Characterizing school-linked and non-school linked SARS-CoV-2 cases in children and households: a retrospective cohort study using linked population-level administrative data from Manitoba, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Respiratory viral infections research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; University of Manitoba; Manitoba Health","funders":"","keywords":"Cohort; Retrospective cohort study; Cohort study; Medicine; Population; Linked data; Demography; Pediatrics; Environmental health; Computer science; Sociology; World Wide Web","score_opus":0.2454693793249349,"score_gpt":0.4547403149182998,"score_spread":0.2092709355933649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9929573,0.000114249226,0.0004767142,0.0003169223,0.0009062268,0.001438037,0.0037516067,0.000028753904,0.000010183623],"genre_scores_gemma":[0.99508744,0.000054556807,0.001565134,0.00019629569,0.0007730374,0.000020185755,0.0022572817,0.000028867109,0.000017225808],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9963773,0.00009385139,0.0007756913,0.0010264682,0.0014156371,0.00031104413],"domain_scores_gemma":[0.99809146,0.00018062547,0.0002593303,0.0007083934,0.00051090185,0.00024928228],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0017469537,0.00022862547,0.00034216297,0.0006406744,0.00046291293,0.0012478638,0.0009583905,0.00007664788,0.000023873703],"category_scores_gemma":[0.002795372,0.00021073406,0.000026397744,0.00061474496,0.00014366365,0.0042057573,0.0007366746,0.00065602624,0.0000027763372],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012871592,0.000087799766,0.98979384,0.000007518192,0.00018423545,0.0001471999,0.00005482482,0.000015065507,0.008485941,0.00001604531,0.00023764634,0.0008411724],"study_design_scores_gemma":[0.0009860105,0.0001584092,0.95955646,0.00026972848,0.00008152046,0.00054116757,0.00019250133,0.037774593,0.000090744405,0.00008986471,0.0000652173,0.00019377717],"about_ca_topic_score_codex":0.42890236,"about_ca_topic_score_gemma":0.30049416,"teacher_disagreement_score":0.1284082,"about_ca_system_score_codex":0.0015295311,"about_ca_system_score_gemma":0.0015703754,"threshold_uncertainty_score":0.99978894},"labels":[],"label_agreement":null},{"id":"W4402406162","doi":"10.23889/ijpds.v9i5.2549","title":"Identifying hospitalization episodes of care among people with and without HIV in British Columbia, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"HIV/AIDS Research and Interventions","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University; AIDS Vancouver","funders":"","keywords":"Human immunodeficiency virus (HIV); Medicine; History; Demography; Gerontology; Pediatrics; Family medicine; Sociology","score_opus":0.02373057883706946,"score_gpt":0.3604041760842211,"score_spread":0.3366735972471516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406162","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99084055,0.00032533167,0.0076465593,0.00025304672,0.00024305393,0.00019657216,0.00039969842,0.0000070618917,0.00008812893],"genre_scores_gemma":[0.9971688,0.00007241898,0.0013152763,0.000010504562,0.000065135166,0.0000063509037,0.0005109791,0.0000069348202,0.0008436423],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99865264,0.000013030469,0.00026586614,0.00021105642,0.0007192585,0.00013817196],"domain_scores_gemma":[0.9991613,0.000025137177,0.00007576544,0.00011538508,0.0005213331,0.000101064936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040196485,0.00003930899,0.00009883648,0.00019567425,0.00012350209,0.0006607365,0.00030093172,0.0000152115545,0.00005019144],"category_scores_gemma":[0.00044952452,0.000046143843,0.000019882878,0.0003161754,0.00009942485,0.0015108183,0.00009290733,0.00010173576,2.6539396e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012548204,0.000013867965,0.9887808,0.000080978396,0.000020140784,0.000017518872,0.00015962402,0.000030938452,0.00009092289,0.00008519637,0.0017947917,0.008912675],"study_design_scores_gemma":[0.00039388554,0.00014333145,0.95602673,0.001396806,0.000015127473,0.00022251176,0.00074890803,0.040379196,0.000027853428,0.00012125326,0.00046980675,0.000054581717],"about_ca_topic_score_codex":0.59877414,"about_ca_topic_score_gemma":0.9789517,"teacher_disagreement_score":0.38017756,"about_ca_system_score_codex":0.00024113944,"about_ca_system_score_gemma":0.0005798039,"threshold_uncertainty_score":0.63714975},"labels":[],"label_agreement":null},{"id":"W4402406168","doi":"10.23889/ijpds.v9i5.2679","title":"Impact of out-of-home care on children’s outcomes: A longitudinal cohort study using linked administrative data from Manitoba, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; McGill University; University of Toronto; First Nations Health and Social Secretariat of Manitoba; Assembly of Manitoba Chiefs; Government of Manitoba; University of Manitoba","funders":"","keywords":"Cohort; Longitudinal data; Gerontology; Cohort study; Longitudinal study; Medicine; Demography; Sociology","score_opus":0.2803903807187301,"score_gpt":0.5382044534984339,"score_spread":0.2578140727797038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9718294,0.00008942602,0.00060832466,0.000120839824,0.009472451,0.00067126646,0.01717756,0.000012210965,0.000018533727],"genre_scores_gemma":[0.99529,0.00000589624,0.0004926354,0.000011817635,0.0005840133,0.000004512419,0.0035802086,0.000012292562,0.000018620512],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971245,0.00009456989,0.00076691766,0.00050723396,0.0012759881,0.00023077943],"domain_scores_gemma":[0.9974207,0.0004231699,0.0004951294,0.0007589377,0.00078841875,0.0001135882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086771493,0.00014416646,0.0002817074,0.0003102514,0.00040120014,0.00009855952,0.0020368407,0.000045479977,0.00008641877],"category_scores_gemma":[0.0005198802,0.000109319626,0.00006452893,0.00026020376,0.0000696895,0.001070079,0.00045151732,0.00031271213,0.0000023312523],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000090117,0.00007268475,0.99500483,0.000007946169,0.00026154926,0.000010483392,0.0013052952,0.00014222768,0.000026576252,0.00003961886,0.0019489919,0.0010896738],"study_design_scores_gemma":[0.00044264438,0.00016449872,0.9932661,0.00023009721,0.00010417393,0.000008691891,0.002949799,0.002583061,0.000002927621,0.0000964272,0.000048072685,0.00010349305],"about_ca_topic_score_codex":0.5226894,"about_ca_topic_score_gemma":0.46730983,"teacher_disagreement_score":0.055379584,"about_ca_system_score_codex":0.0011803487,"about_ca_system_score_gemma":0.0034025626,"threshold_uncertainty_score":0.60359997},"labels":[],"label_agreement":null},{"id":"W4402406175","doi":"10.23889/ijpds.v9i5.2708","title":"Neighborhood-level sociodemographics and kindergarten children’s developmental vulnerability, pre- and post-COVID-19 in Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Wilfrid Laurier University; University of British Columbia; McMaster University","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Vulnerability (computing); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Psychology; Developmental psychology; Environmental health; Medicine; Computer science; Computer security; Outbreak","score_opus":0.05914688762431338,"score_gpt":0.3915766291420541,"score_spread":0.33242974151774074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406175","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9675503,0.00027768878,0.0014594583,0.027525371,0.002250687,0.00029600452,0.00044699,0.000024488367,0.00016901792],"genre_scores_gemma":[0.99462265,0.00023436433,0.003015845,0.0015876439,0.0002101915,0.0000060362127,0.00020147214,0.0000058961195,0.000115920426],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980216,0.000059468683,0.00033880002,0.00040182009,0.0009334225,0.00024487876],"domain_scores_gemma":[0.9990639,0.00020445693,0.00008521239,0.00009919179,0.00021060776,0.0003365924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002200913,0.00009433766,0.00008635703,0.00035471786,0.0008012371,0.0008317208,0.00074199616,0.00003719253,0.000056809975],"category_scores_gemma":[0.0012627722,0.00009006565,0.000015912163,0.0003630514,0.00022956547,0.0018578486,0.00022293525,0.00018650269,9.360539e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009179978,0.00001554743,0.9480285,0.0000052794376,0.0000206389,0.0000032399262,0.0050624474,0.000026375319,0.000014002962,0.018888747,0.0014870133,0.026439017],"study_design_scores_gemma":[0.0001994179,0.0000070306755,0.98099786,0.00002527151,0.000004439606,0.00008435824,0.001428375,0.00073846785,0.000001508666,0.0050285305,0.011357239,0.00012751664],"about_ca_topic_score_codex":0.5712938,"about_ca_topic_score_gemma":0.82498616,"teacher_disagreement_score":0.2536924,"about_ca_system_score_codex":0.0015003327,"about_ca_system_score_gemma":0.013145056,"threshold_uncertainty_score":0.9924495},"labels":[],"label_agreement":null},{"id":"W4402406251","doi":"10.23889/ijpds.v9i5.2528","title":"Comparing health service use before and after transition to a supported housing model for clients who experience severe and persistent mental illness in southwestern Ontario, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Mental Health Treatment and Access","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Mental illness; Mental health; Service (business); Transition (genetics); Mental health service; Psychiatry; Psychology; Business; Gerontology; Medicine; Marketing","score_opus":0.10610955851671944,"score_gpt":0.4097852042524347,"score_spread":0.30367564573571526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406251","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9925904,0.00003836029,0.0027639198,0.0019417885,0.0013249362,0.00053650356,0.0007936412,0.0000072953794,0.0000031140182],"genre_scores_gemma":[0.9972549,0.00000405426,0.00084426545,0.0011838046,0.000047658057,0.000046126544,0.0004825912,0.00000833388,0.00012828026],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986627,0.00001506177,0.00033106445,0.00039125702,0.00035531778,0.0002445678],"domain_scores_gemma":[0.9995247,0.000024452342,0.00008074951,0.00011169914,0.00008784209,0.00017055236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003448859,0.00009985028,0.000115643095,0.0001930823,0.00032316195,0.00039829142,0.00028209703,0.000020792533,0.000019762749],"category_scores_gemma":[0.000008416502,0.00009222979,0.000017040498,0.00012810553,0.00002732303,0.0016986025,0.000101657184,0.00007840791,3.2600425e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009993786,0.00011852451,0.8679984,0.00011844947,0.000059867765,0.000032086602,0.09254193,0.0029188164,0.00002933285,0.00032587416,0.0005427285,0.03431458],"study_design_scores_gemma":[0.0008877294,0.00007119922,0.5350487,0.0003505896,0.000011030191,0.00012892573,0.0020664628,0.46076035,0.0000020566,0.00008775498,0.00045207483,0.00013311017],"about_ca_topic_score_codex":0.49732465,"about_ca_topic_score_gemma":0.9497874,"teacher_disagreement_score":0.45784155,"about_ca_system_score_codex":0.0008250832,"about_ca_system_score_gemma":0.00023329597,"threshold_uncertainty_score":0.5060227},"labels":[],"label_agreement":null},{"id":"W4402406255","doi":"10.23889/ijpds.v9i5.2543","title":"Prevalence of Multimorbidity and Chronic Diseases in citizens of the Métis Nation of Ontario","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Métis National Council","funders":"","keywords":"Multimorbidity; Environmental health; Medicine; Geography; Chronic disease; Family medicine","score_opus":0.08738202536390065,"score_gpt":0.4023462714164732,"score_spread":0.31496424605257256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406255","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99682367,0.0004480851,0.00060797454,0.00045298837,0.000888241,0.00023466628,0.00042597664,0.000004202097,0.00011421736],"genre_scores_gemma":[0.99919957,0.000107482934,0.00038738703,0.000007731183,0.0000639798,0.0000020968323,0.00005513985,0.0000027042581,0.00017388843],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988414,0.00001116994,0.00031816663,0.00015487624,0.00060078467,0.00007360775],"domain_scores_gemma":[0.9993359,0.00005707009,0.00017420317,0.00019221123,0.00021047147,0.000030131969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044407585,0.000045872323,0.000084554136,0.0002223741,0.000033738273,0.000036747937,0.00044459698,0.000011864301,0.00007325947],"category_scores_gemma":[0.0003733859,0.000033521625,0.000036070538,0.00019249,0.000210935,0.00072579476,0.00021470682,0.00006328504,1.5395278e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013246205,0.0001791037,0.9502336,0.0012092128,0.00008379789,0.0000070572423,0.0003726139,0.0014580792,0.0054007615,0.02626912,0.00047673017,0.0141774565],"study_design_scores_gemma":[0.00042929736,0.000044469263,0.96504706,0.0007925232,0.000059100395,0.000015514548,0.000023686365,0.031140331,0.0004392123,0.0016662761,0.00031198576,0.00003053375],"about_ca_topic_score_codex":0.0017247378,"about_ca_topic_score_gemma":0.0015490117,"teacher_disagreement_score":0.02968225,"about_ca_system_score_codex":0.00038163108,"about_ca_system_score_gemma":0.00089225575,"threshold_uncertainty_score":0.2607299},"labels":[],"label_agreement":null},{"id":"W4402406263","doi":"10.23889/ijpds.v9i5.2525","title":"Long-term trends in co-occurring medical and psychiatric hospitalizations among children and adolescents in Ontario, Canada.","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child and Adolescent Health","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Centre for Addiction and Mental Health; Women's College Hospital; University of Toronto; Hospital for Sick Children","funders":"","keywords":"Term (time); Psychiatry; Co-occurrence; Medicine; Pediatrics; Psychology; Computer science","score_opus":0.03803648782358963,"score_gpt":0.43304669883330155,"score_spread":0.3950102110097119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99514383,0.00021418095,0.00028649546,0.001564924,0.00232781,0.00021924269,0.00019068192,0.000011487203,0.000041368035],"genre_scores_gemma":[0.998529,0.000116098556,0.000097920034,0.00040185376,0.00029938918,0.0000017720643,0.00048676122,0.000007737088,0.00005947527],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980335,0.000051026273,0.00054825895,0.0003548011,0.00072696153,0.00028541713],"domain_scores_gemma":[0.9993794,0.00005838822,0.00012551325,0.00013371716,0.00007242721,0.00023057668],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011505296,0.00009250845,0.00011891043,0.0007190551,0.00039340378,0.00012429369,0.0005430231,0.00005756879,0.00009795436],"category_scores_gemma":[0.00021578089,0.000082783634,0.000012689661,0.000382908,0.00007201147,0.0010922756,0.00020440051,0.00058268424,6.845035e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010730184,0.000025163241,0.99031323,0.000021001586,0.000003887419,0.000013049559,0.00023638921,0.000011783197,5.33729e-7,0.00045215565,0.0009894773,0.00792258],"study_design_scores_gemma":[0.0006387792,0.000008927684,0.9923955,0.0011486427,0.000004287848,0.00003091682,0.000039233208,0.0052678366,9.913875e-8,0.00010841007,0.00027320464,0.00008413669],"about_ca_topic_score_codex":0.5358817,"about_ca_topic_score_gemma":0.9793241,"teacher_disagreement_score":0.4434424,"about_ca_system_score_codex":0.00069158385,"about_ca_system_score_gemma":0.0016236748,"threshold_uncertainty_score":0.46720892},"labels":[],"label_agreement":null},{"id":"W4402406276","doi":"10.23889/ijpds.v9i5.2522","title":"Expanding a cohort of children who had a response to the Household Food Security Survey Module: A novel approach using linked ICES administrative data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"St Joseph's Health Care; Western University","funders":"","keywords":"Cohort; Food security; Survey data collection; Environmental health; Business; Computer science; Data science; Computer security; Geography; Medicine; Statistics; Mathematics; Agriculture","score_opus":0.5799653690778103,"score_gpt":0.5555590051684497,"score_spread":0.024406363909360573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9156145,0.00012377779,0.043358803,0.002470947,0.0031325803,0.0014965333,0.03370613,0.000046010187,0.000050706803],"genre_scores_gemma":[0.9868319,0.000028924109,0.009475598,0.00027970827,0.0006566448,0.000028345823,0.0026366846,0.00001963716,0.000042581203],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9959494,0.0005499559,0.0010409959,0.00071259757,0.0013126427,0.00043439318],"domain_scores_gemma":[0.9958829,0.0012502305,0.0005488782,0.0013066677,0.00078019284,0.00023108869],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.016432604,0.00016782132,0.00025349946,0.00056122115,0.001975223,0.000335606,0.00475637,0.00010853055,0.000025162753],"category_scores_gemma":[0.007018386,0.00013054338,0.000051023053,0.0009727131,0.00018430024,0.0028244047,0.0020070616,0.00066725654,0.0000048639195],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0043126484,0.000706095,0.90700746,0.0003129591,0.00087787776,0.0000068800355,0.021511108,0.011816108,0.0009893639,0.026892947,0.024130568,0.0014360064],"study_design_scores_gemma":[0.00056583603,0.00015703557,0.66113824,0.00056690525,0.00006246117,0.000054422388,0.00094593194,0.33295423,0.000010160239,0.0008597692,0.0024773697,0.00020767788],"about_ca_topic_score_codex":0.0023858184,"about_ca_topic_score_gemma":0.0018066224,"teacher_disagreement_score":0.3211381,"about_ca_system_score_codex":0.00035419743,"about_ca_system_score_gemma":0.0015484061,"threshold_uncertainty_score":0.9993241},"labels":[],"label_agreement":null},{"id":"W4402406287","doi":"10.23889/ijpds.v9i5.2493","title":"Applying Newly Identified Financially Focused Home Care Quality and Performance Indicators In Alberta's $23.5B/annum Health System - Preliminary Findings","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Quality (philosophy); Business; Actuarial science; Environmental health; Environmental economics; Operations management; Medicine; Economics","score_opus":0.0952740969448424,"score_gpt":0.37443885404462146,"score_spread":0.27916475709977906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406287","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9724792,0.001604722,0.008515133,0.009860516,0.0053288117,0.000907429,0.0008634134,0.00004578328,0.0003949455],"genre_scores_gemma":[0.99781185,0.00021513541,0.0010209687,0.00031229306,0.00021172555,0.000052293104,0.00021861514,0.000012187846,0.00014491039],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9979168,0.000024391047,0.0009785024,0.000533047,0.00022774274,0.00031947298],"domain_scores_gemma":[0.9990647,0.000094329596,0.0003676416,0.00026710442,0.00007059918,0.00013565221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032232516,0.000115599185,0.00022395939,0.001440812,0.00037342185,0.0006265836,0.00093100226,0.000048603673,0.0000060514226],"category_scores_gemma":[0.0003452287,0.00012623811,0.000039916788,0.00061527616,0.00006052253,0.0023746546,0.00030345388,0.00019218253,0.000021541273],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000093096554,0.00003525946,0.24260628,0.0008120639,0.00003334326,0.000009164514,0.0027229094,0.00041350775,0.0000036161664,0.6527772,0.00067944435,0.09981413],"study_design_scores_gemma":[0.00076969137,0.00014993812,0.8785613,0.0007133935,0.0000051175753,0.00004621502,0.00044409846,0.052560627,0.000008411574,0.005659226,0.06074878,0.000333161],"about_ca_topic_score_codex":0.0065705776,"about_ca_topic_score_gemma":0.0009238462,"teacher_disagreement_score":0.647118,"about_ca_system_score_codex":0.00075223396,"about_ca_system_score_gemma":0.00023504574,"threshold_uncertainty_score":0.99327916},"labels":[],"label_agreement":null},{"id":"W4402406304","doi":"10.23889/ijpds.v9i5.2896","title":"Comparing terminology mappings to ICD-10 coded data in Discharge Abstract Database (DAD) in Alberta, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"","keywords":"Terminology; Database; Computer science; Data mining; Linguistics","score_opus":0.0781127730537302,"score_gpt":0.3860818542312556,"score_spread":0.30796908117752536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406304","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9868625,0.00021639407,0.003952591,0.005078501,0.0023885502,0.00014278451,0.0012282616,0.000007618762,0.00012279056],"genre_scores_gemma":[0.99259037,0.00002763063,0.0027545209,0.00025327978,0.00022750234,0.0000043586897,0.0038812442,0.000006218249,0.00025485287],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99850434,0.00001566269,0.00035367938,0.0005208544,0.00036208035,0.00024337665],"domain_scores_gemma":[0.99919266,0.000066808374,0.00007058607,0.0005006856,0.00007039616,0.00009886739],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089607696,0.00009003475,0.00010488289,0.00022824605,0.00007032007,0.00017351213,0.0023135701,0.000045462617,0.000027592923],"category_scores_gemma":[0.0014243071,0.00007993287,0.000012932753,0.00019165404,0.00007982284,0.00010743109,0.0010010942,0.0001473552,0.000004919075],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000724547,0.00035394126,0.48974258,0.00013909795,0.00018051115,0.00042300505,0.00039458825,0.0020137469,0.13259752,0.0031612953,0.181424,0.18884516],"study_design_scores_gemma":[0.00086118287,0.0000757785,0.3708576,0.00038301287,0.000010026068,0.00026729496,0.0001677237,0.09818601,0.0012655236,0.000250375,0.5272882,0.00038726855],"about_ca_topic_score_codex":0.12504254,"about_ca_topic_score_gemma":0.6026233,"teacher_disagreement_score":0.47758076,"about_ca_system_score_codex":0.00010542765,"about_ca_system_score_gemma":0.0005412315,"threshold_uncertainty_score":0.88078386},"labels":[],"label_agreement":null},{"id":"W4402406346","doi":"10.23889/ijpds.v9i5.2911","title":"Evaluating Health Canada’s Proposed Front-of-Pack Labelling Policy:   Burden of Healthcare Use Attributed to Health Canada’s Proposed Front-of-Pack Labelling Policy","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Labelling; Front (military); Business; Engineering; Psychology; Mechanical engineering","score_opus":0.22126998773151582,"score_gpt":0.43797233368288657,"score_spread":0.21670234595137075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406346","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22882427,0.004687334,0.07934391,0.6353567,0.009450303,0.0041716937,0.037935823,0.00007606802,0.0001538699],"genre_scores_gemma":[0.97759044,0.00040667583,0.01804209,0.0023745485,0.0006336597,0.000006865428,0.00063836615,0.00003329812,0.00027405648],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99525034,0.00010753764,0.0023638909,0.0006835723,0.0008531047,0.00074156397],"domain_scores_gemma":[0.9961485,0.0001875572,0.0017194609,0.00058296806,0.0008359615,0.0005255237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049775657,0.00022308642,0.0006382421,0.0012874808,0.00043664346,0.0002106072,0.0015425748,0.000057203328,0.000023301873],"category_scores_gemma":[0.0026041104,0.00023830342,0.00007674801,0.00083803653,0.0000808949,0.001093611,0.00032835605,0.00028099396,0.0000034411225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.0003864855,0.00026506733,0.032047063,0.0037351982,0.00064865855,0.000020187812,0.008688675,0.10107453,0.00042117896,0.6694098,0.03975303,0.1435501],"study_design_scores_gemma":[0.00236562,0.0010980545,0.04622292,0.003756815,0.00003142164,0.000055041175,0.0012013682,0.6064239,0.00051182625,0.017179098,0.32002684,0.0011270662],"about_ca_topic_score_codex":0.997628,"about_ca_topic_score_gemma":0.9769657,"teacher_disagreement_score":0.7487662,"about_ca_system_score_codex":0.0045885816,"about_ca_system_score_gemma":0.024960497,"threshold_uncertainty_score":0.99923265},"labels":[],"label_agreement":null},{"id":"W4402406384","doi":"10.23889/ijpds.v9i5.2894","title":"Barriers and enablers to secondary use of multi-regional linked administrative health data for three distinct user groups: academic researchers, health-system knowledge users, and private sector researchers","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Public Health Agency of Canada; Canadian Agency for Drugs and Technologies in Health; University of New Brunswick","funders":"","keywords":"Business; Health data; Knowledge management; Data science; Public relations; Computer science; Health care; Political science","score_opus":0.6037436785662871,"score_gpt":0.5918827835266478,"score_spread":0.011860895039639274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406384","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43380404,0.012220287,0.13704434,0.30911714,0.013574827,0.01453894,0.07929396,0.00031883336,0.00008764328],"genre_scores_gemma":[0.9206033,0.0018281625,0.05922235,0.008159972,0.0021003226,0.00029250555,0.006536167,0.00012170926,0.0011355252],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9956254,0.00045019263,0.001238397,0.00088796474,0.0010089789,0.00078906043],"domain_scores_gemma":[0.9945038,0.002399429,0.0005096024,0.0006757619,0.00079920696,0.001112189],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.011574649,0.0001958729,0.00038444906,0.0007354342,0.0016589015,0.00025968574,0.0020077683,0.00013297997,0.000032827513],"category_scores_gemma":[0.00399269,0.0001664384,0.000043357373,0.00051267596,0.00034849378,0.0036870213,0.0015715947,0.0010864577,0.0000037966959],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003134351,0.00010968186,0.31880578,0.0067993635,0.0005199383,0.000020315068,0.0135563435,0.00005306397,0.00049294916,0.052003633,0.47279242,0.13171215],"study_design_scores_gemma":[0.0021499887,0.00052782847,0.34058216,0.0020826745,0.000024976547,0.000050607672,0.0031417315,0.05759624,0.0000033334654,0.0007960603,0.59272426,0.0003201387],"about_ca_topic_score_codex":0.0015609195,"about_ca_topic_score_gemma":0.0058313212,"teacher_disagreement_score":0.48679927,"about_ca_system_score_codex":0.0017106176,"about_ca_system_score_gemma":0.010736555,"threshold_uncertainty_score":0.9996408},"labels":[],"label_agreement":null},{"id":"W4402406389","doi":"10.23889/ijpds.v9i5.2897","title":"Association between neighbourhood poverty and type 2 diabetes risk. Does moving from a high to lower poverty neighbourhood reduce diabetes risk?","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Public Health Policies and Epidemiology","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of Toronto","funders":"","keywords":"Neighbourhood (mathematics); Poverty; Type 2 diabetes; Diabetes mellitus; Environmental health; Medicine; Association (psychology); Psychology; Economics; Endocrinology; Mathematics; Economic growth","score_opus":0.028051031819882086,"score_gpt":0.3309239338955715,"score_spread":0.3028729020756894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406389","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94433284,0.00012788453,0.0010916626,0.043434955,0.008941017,0.00022251338,0.0015603991,0.000080393474,0.00020834517],"genre_scores_gemma":[0.9829247,0.000109893124,0.0011635592,0.009491831,0.005563164,0.000006256584,0.00065336406,0.000020029598,0.000067230954],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973781,0.00005067273,0.0006328891,0.0006002499,0.00075757806,0.0005804973],"domain_scores_gemma":[0.9976836,0.0006437925,0.0006361767,0.0003034258,0.0006215179,0.00011149048],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0032614863,0.00019151568,0.00026835248,0.00047004397,0.00064732484,0.0021267314,0.0011776403,0.00010232362,0.00020356638],"category_scores_gemma":[0.009503851,0.00014142467,0.00006368008,0.0006227654,0.00004418175,0.0055279452,0.0007438718,0.00033181655,0.000059175196],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001827974,0.000022193228,0.8875396,0.000018625815,0.00014397013,0.0000010688334,0.000021442142,0.00043160436,0.00014960012,0.0029290167,0.086963475,0.021761099],"study_design_scores_gemma":[0.00022828196,0.000025179545,0.7664682,0.00009722181,0.00009447292,5.389215e-7,0.000029151346,0.077060565,0.000008967022,0.0188917,0.13690749,0.00018820282],"about_ca_topic_score_codex":0.012702188,"about_ca_topic_score_gemma":0.0003312668,"teacher_disagreement_score":0.121071406,"about_ca_system_score_codex":0.00033947278,"about_ca_system_score_gemma":0.00010146267,"threshold_uncertainty_score":0.9989092},"labels":[],"label_agreement":null},{"id":"W4402406434","doi":"10.23889/ijpds.v9i5.2517","title":"Family Matters: Enhancing Insight in Linked Administrative Data Through Familial Linkage","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Victoria Park","funders":"","keywords":"Linked data; Linkage (software); Computer science; Business; Psychology; Genetics; World Wide Web; Biology; Gene","score_opus":0.2446603651613526,"score_gpt":0.39945938874275644,"score_spread":0.15479902358140385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406434","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2815099,0.0039154547,0.6299863,0.015858512,0.024712747,0.00076607085,0.039387155,0.00012738915,0.0037364673],"genre_scores_gemma":[0.9845919,0.00042134034,0.008054226,0.0008405764,0.00089602807,0.0000059789127,0.004995133,0.000013762353,0.00018103483],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978314,0.0000160172,0.00089735567,0.0007691373,0.00024738177,0.00023867893],"domain_scores_gemma":[0.99868995,0.00013746938,0.00028331182,0.0007060499,0.00011010763,0.00007313328],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001847154,0.00012867099,0.00021581889,0.00059840875,0.00018888069,0.0011217424,0.003185752,0.00005545738,0.000147351],"category_scores_gemma":[0.0006706021,0.0001283238,0.000053959266,0.0006322388,0.00009656312,0.007419285,0.0006431698,0.00024248345,0.00013657259],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051058346,0.0008540979,0.18827975,0.0002454295,0.0013259993,0.00063641695,0.00897931,0.0047605685,0.007947029,0.63683677,0.05813303,0.09149103],"study_design_scores_gemma":[0.0007850256,0.000082801365,0.11063592,0.000309624,0.000031893243,0.00007734738,0.0003599152,0.5523929,0.000101231395,0.046239886,0.2884307,0.00055279414],"about_ca_topic_score_codex":0.0021820578,"about_ca_topic_score_gemma":0.0009044261,"teacher_disagreement_score":0.703082,"about_ca_system_score_codex":0.0001955905,"about_ca_system_score_gemma":0.00014705447,"threshold_uncertainty_score":0.9999152},"labels":[],"label_agreement":null},{"id":"W4402406471","doi":"10.23889/ijpds.v9i5.2878","title":"Validated Administrative Data-Based ICD-10 Algorithms for Chronic Conditions","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Algorithm; Data mining","score_opus":0.6434628105406506,"score_gpt":0.6449304775123317,"score_spread":0.001467666971681103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406471","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052180476,0.00023189606,0.91075426,0.026322829,0.023204777,0.0021586232,0.030781055,0.0002672083,0.0010613265],"genre_scores_gemma":[0.8741656,0.0000857234,0.038437523,0.0026305253,0.006009767,0.00026163814,0.07592439,0.000038026374,0.0024468105],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971575,0.00008344264,0.0009376165,0.00044376307,0.0009571537,0.00042053353],"domain_scores_gemma":[0.99659723,0.0010955327,0.00038954237,0.0005642815,0.0010866285,0.00026680523],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004992981,0.00012108875,0.00014756178,0.00042290238,0.0018301186,0.00032013538,0.0021335096,0.00009682738,0.00092860905],"category_scores_gemma":[0.003323086,0.000100516096,0.00004267528,0.00035453867,0.0001457801,0.0035375317,0.0002702582,0.00043179438,0.00013488925],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044116174,0.00016927862,0.0017930516,0.0010538909,0.00019742094,0.000017246713,0.0010385327,0.0017133413,0.00067271583,0.090608604,0.81156427,0.090730496],"study_design_scores_gemma":[0.0006151396,0.00009786025,0.001496333,0.00041981525,0.000023297209,0.000011386579,0.0001159808,0.6204341,0.00002410232,0.0019272886,0.3747378,0.00009692734],"about_ca_topic_score_codex":0.000073851224,"about_ca_topic_score_gemma":0.00009792468,"teacher_disagreement_score":0.8723167,"about_ca_system_score_codex":0.000631743,"about_ca_system_score_gemma":0.0039133625,"threshold_uncertainty_score":0.9999847},"labels":[],"label_agreement":null},{"id":"W4402406476","doi":"10.23889/ijpds.v9i5.2872","title":"Addressing data gaps on long-term care in Canada through data linkage","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Term (time); Linkage (software); Record linkage; Computer science; Data science; Business; Medicine; Environmental health; Biology; Genetics","score_opus":0.5619007749469208,"score_gpt":0.5650601188922989,"score_spread":0.0031593439453780903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406476","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31727976,0.0063861446,0.31795397,0.04661607,0.10431838,0.0025263154,0.19857016,0.00021493259,0.0061342735],"genre_scores_gemma":[0.97438085,0.00017197315,0.0042544752,0.000988282,0.00072143885,0.0000028332552,0.019235743,0.000012713461,0.00023171127],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9928875,0.000116963914,0.0009840365,0.0014027874,0.0042764726,0.0003322556],"domain_scores_gemma":[0.9946123,0.0007785897,0.00031351246,0.0037551,0.00041172412,0.00012878327],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.007643748,0.00014997055,0.00018051591,0.00053581403,0.00038612942,0.003969571,0.021719158,0.00003135393,0.00019140517],"category_scores_gemma":[0.00577839,0.000117880285,0.00002487575,0.0008914254,0.00011871433,0.015062886,0.0065731937,0.00030619878,0.000046940087],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011867532,0.000086969754,0.03872764,0.000060798757,0.000067810266,0.00045494956,0.0005733267,0.002581241,0.00005047676,0.015561203,0.20476794,0.73694897],"study_design_scores_gemma":[0.0007501902,0.000053457792,0.19660865,0.0010975983,0.000037753052,0.00013111878,0.0018590741,0.26192424,0.00004262862,0.008945253,0.5280487,0.0005013468],"about_ca_topic_score_codex":0.13719052,"about_ca_topic_score_gemma":0.68050826,"teacher_disagreement_score":0.73644763,"about_ca_system_score_codex":0.00072396797,"about_ca_system_score_gemma":0.0019889413,"threshold_uncertainty_score":0.9987129},"labels":[],"label_agreement":null},{"id":"W4402406478","doi":"10.23889/ijpds.v9i5.2860","title":"Building access to linked data for program evaluation: lessons and opportunities from the evaluation of a pan-Canadian skills training initiative","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Computer science; Medical education; Data science; Medicine; Geography","score_opus":0.8689239634490931,"score_gpt":0.6757502367984896,"score_spread":0.1931737266506035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.530537,0.0013421035,0.26061788,0.15847363,0.0149279125,0.0094226,0.023628602,0.00007261344,0.0009776655],"genre_scores_gemma":[0.97890884,0.00006171238,0.017651621,0.00079393137,0.00058491173,0.00020069767,0.0017648172,0.000009436452,0.000024010276],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99309707,0.00023379881,0.0008652464,0.0006783147,0.0048871543,0.00023841532],"domain_scores_gemma":[0.9916089,0.0022262859,0.00043169074,0.000846199,0.0046900637,0.00019682599],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.043027993,0.0001231875,0.00016682732,0.00076899724,0.00067116605,0.0038322143,0.0048137223,0.00004173966,0.0002570527],"category_scores_gemma":[0.015298864,0.000084752886,0.000044259647,0.0006356353,0.00016695194,0.007935572,0.0006828477,0.00013289753,0.0000036707522],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017339875,0.000019024774,0.0012698676,0.0000021085132,0.00004610923,3.681348e-7,0.0011117744,0.001983925,0.000054732616,0.0059336713,0.0043115956,0.98524946],"study_design_scores_gemma":[0.0003977869,0.000049193484,0.084866226,0.00014417685,0.00009566598,0.000010572754,0.0012705153,0.8021897,0.000016097294,0.041623894,0.06923282,0.0001033486],"about_ca_topic_score_codex":0.0011395444,"about_ca_topic_score_gemma":0.010342628,"teacher_disagreement_score":0.9851461,"about_ca_system_score_codex":0.00029862515,"about_ca_system_score_gemma":0.004410879,"threshold_uncertainty_score":0.9972019},"labels":[],"label_agreement":null},{"id":"W4402406479","doi":"10.23889/ijpds.v9i5.2865","title":"Efficiency gains from the implementation of Research IDs for data linkage: A case study from Population Data BC and the Data Innovation Program in British Columbia, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Linkage (software); Record linkage; Linked data; Population; Computer science; Data science; Research data; World Wide Web; Demography; Biology; Sociology; Genetics; Data curation","score_opus":0.4921450913277475,"score_gpt":0.6045446402558524,"score_spread":0.11239954892810494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406479","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90049005,0.00018364341,0.021743303,0.0052850856,0.002354611,0.0026317788,0.06728862,0.000016862525,0.0000060587113],"genre_scores_gemma":[0.9493558,0.00003834852,0.0040356074,0.00014844105,0.0003897671,0.00004251696,0.045942806,0.000009955093,0.00003680508],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99197733,0.0005668273,0.0016822978,0.0014664421,0.004002493,0.00030463043],"domain_scores_gemma":[0.98948175,0.0045466796,0.0006070544,0.0040706955,0.0012275538,0.00006625866],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["metaresearch","open_science"],"category_scores_codex":[0.043939915,0.000107991495,0.00022163712,0.00036601728,0.0010184221,0.00774277,0.014782037,0.00003554312,0.00006461908],"category_scores_gemma":[0.014803424,0.00009015787,0.000016946538,0.0022678475,0.00036932318,0.008259815,0.008567214,0.00031121858,9.868891e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000076963246,0.00023551534,0.23483013,0.000014085735,0.000109244895,0.00009413893,0.00089431123,0.00009522119,0.000009856028,0.0023319442,0.07071202,0.6905966],"study_design_scores_gemma":[0.0017624174,0.00007547489,0.350284,0.00010801156,0.00006503086,0.00006599552,0.021288028,0.5814206,8.009869e-7,0.015291888,0.02948316,0.00015456663],"about_ca_topic_score_codex":0.97160274,"about_ca_topic_score_gemma":0.99270624,"teacher_disagreement_score":0.690442,"about_ca_system_score_codex":0.00020205289,"about_ca_system_score_gemma":0.0010170622,"threshold_uncertainty_score":0.9994513},"labels":[],"label_agreement":null},{"id":"W4402406483","doi":"10.23889/ijpds.v9i5.2846","title":"Model-based algorithms to ascertain smoking in administrative health data: a registry-based validation study","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Data mining; Algorithm; Data science","score_opus":0.5534976125645847,"score_gpt":0.586329769139679,"score_spread":0.03283215657509431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406483","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12409365,0.00004178895,0.86300874,0.008535062,0.0023847842,0.0005725365,0.0012757323,0.000046701494,0.000041007344],"genre_scores_gemma":[0.96192163,0.0000044241115,0.036022384,0.0005029712,0.00019103196,0.000021832755,0.0012636583,0.000013444762,0.000058591588],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9930546,0.0002030032,0.0013484467,0.0012630667,0.0037947455,0.0003360868],"domain_scores_gemma":[0.9961015,0.0006997892,0.00048358613,0.001295641,0.0011846719,0.00023478756],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.019952545,0.00016923393,0.00022818027,0.0018440541,0.0004604454,0.0031524613,0.00499732,0.00004269128,0.00002329265],"category_scores_gemma":[0.006361574,0.00014119134,0.000052680887,0.0024076307,0.00008255822,0.0040246127,0.0003721268,0.00025587346,0.0000110340925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018008502,0.00036039486,0.021909166,0.000010230176,0.00002852033,0.000028596623,0.00089137786,0.8369414,0.00009654586,0.0031749539,0.0041378206,0.1322409],"study_design_scores_gemma":[0.0004905321,0.00015573487,0.00890329,0.00013592561,0.0000094471625,0.000010928907,0.0007782762,0.98051643,0.000013089984,0.0074844756,0.0013534223,0.00014847124],"about_ca_topic_score_codex":0.0004724411,"about_ca_topic_score_gemma":0.0010399405,"teacher_disagreement_score":0.83782804,"about_ca_system_score_codex":0.00037527946,"about_ca_system_score_gemma":0.0019418796,"threshold_uncertainty_score":0.99788237},"labels":[],"label_agreement":null},{"id":"W4402406486","doi":"10.23889/ijpds.v9i5.2867","title":"Creating a Data Cleaning and Pre-Processing Module for Generalisable Data Linkage","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta; University of Calgary; Alberta Health; Alberta Health Services","funders":"","keywords":"Linkage (software); Database; Data processing; Computer science; Process engineering; Engineering; Chemistry","score_opus":0.4833771817173695,"score_gpt":0.5563532414405485,"score_spread":0.07297605972317905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406486","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015870199,0.0005829029,0.96248245,0.0044142157,0.0039001973,0.00038318522,0.012040771,0.000058075944,0.00026803112],"genre_scores_gemma":[0.7222004,0.00016369503,0.25846788,0.00075796404,0.002233456,0.000011655722,0.014250579,0.00002810961,0.0018862599],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99541,0.000058511396,0.0008503473,0.0013455065,0.0020464403,0.00028917144],"domain_scores_gemma":[0.9959332,0.0008187246,0.0003673956,0.0021786133,0.0005591608,0.00014295796],"candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.018859012,0.0001269114,0.00016317275,0.00048018587,0.0009448366,0.008934693,0.011833168,0.000034922672,0.00004662177],"category_scores_gemma":[0.01163909,0.00010027364,0.000026460406,0.0005364728,0.00016251537,0.021402681,0.0066036363,0.00014780984,0.000009650163],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007189693,0.00005082734,0.0016968935,0.000056834608,0.00006035331,0.000010089593,0.00039490085,0.0019042271,0.00047429008,0.035263043,0.08484333,0.87517333],"study_design_scores_gemma":[0.00018753968,0.000017735525,0.0018361699,0.00011324606,0.000023062408,0.00004353309,0.00022446983,0.7818284,0.0000145736085,0.018244782,0.19735579,0.000110692104],"about_ca_topic_score_codex":0.00021343428,"about_ca_topic_score_gemma":0.00019232526,"teacher_disagreement_score":0.87506264,"about_ca_system_score_codex":0.00007241251,"about_ca_system_score_gemma":0.00023066564,"threshold_uncertainty_score":0.9966863},"labels":[],"label_agreement":null},{"id":"W4402406489","doi":"10.23889/ijpds.v9i5.2811","title":"Investigating variation in reported location of death: A comparison of administrative data sources","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"","keywords":"Variation (astronomy); Computer science; Statistics; Data mining; Data science; Mathematics","score_opus":0.6773599503777321,"score_gpt":0.6279318570629745,"score_spread":0.049428093314757615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96433383,0.00039589938,0.025549732,0.002427979,0.004760736,0.0007881241,0.0014542736,0.00003917337,0.00025022667],"genre_scores_gemma":[0.9867293,0.00002553115,0.011291926,0.000050270737,0.00027273654,0.000010148497,0.001584606,0.00000785845,0.00002757194],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967059,0.00015051855,0.0016595545,0.00039623355,0.00087763387,0.00021017302],"domain_scores_gemma":[0.99613565,0.00067233527,0.0011800922,0.0005645676,0.0013560741,0.000091275906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004490602,0.000089868634,0.00020996021,0.00063441676,0.00044405306,0.000068384776,0.0015397534,0.00008552294,0.00004486229],"category_scores_gemma":[0.006812462,0.00008592819,0.000020801848,0.0009409013,0.00013719956,0.0028280634,0.0004611418,0.00038016457,0.00000407404],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009226095,0.00019271456,0.8674459,0.00055682485,0.00008628943,0.0000031994234,0.015589729,0.0038815576,0.0017758136,0.104789525,0.0012092253,0.0043769823],"study_design_scores_gemma":[0.00036774005,0.00006629941,0.5276247,0.0013645248,0.00003302168,0.000008385335,0.0019398757,0.45883405,0.0000587314,0.008123446,0.0014859777,0.000093236384],"about_ca_topic_score_codex":0.0016516969,"about_ca_topic_score_gemma":0.0014086942,"teacher_disagreement_score":0.45495248,"about_ca_system_score_codex":0.00022547685,"about_ca_system_score_gemma":0.0017100539,"threshold_uncertainty_score":0.8155646},"labels":[],"label_agreement":null},{"id":"W4402406507","doi":"10.23889/ijpds.v9i5.2849","title":"Identifying patterns of co-occurring chronic conditions preceding dementia: An unsupervised machine learning approach using health administrative data ","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute of Health Services and Policy Research; Regional Municipality of Waterloo; Sunnybrook Health Science Centre; University of Manitoba; Trillium Health Centre","funders":"","keywords":"Dementia; Unsupervised learning; Computer science; Artificial intelligence; Psychology; Machine learning; Data science; Medicine; Disease","score_opus":0.6244747597443215,"score_gpt":0.6384524637883252,"score_spread":0.01397770404400367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406507","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4568167,0.0008934272,0.52470434,0.0007160248,0.006863766,0.0012066942,0.0085842945,0.0001224783,0.00009226306],"genre_scores_gemma":[0.9788478,0.00013835097,0.01226449,0.0001066829,0.0010305899,0.00001686896,0.0075433482,0.000027995837,0.000023881865],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99583614,0.00042543546,0.001372143,0.0007466328,0.0010980193,0.00052160723],"domain_scores_gemma":[0.9971359,0.00046263597,0.00077982154,0.0006675675,0.0006929881,0.00026108997],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00641337,0.0001646284,0.000238103,0.00052579667,0.003642363,0.0005447743,0.0027379082,0.00007622412,0.0001885781],"category_scores_gemma":[0.0011990049,0.00015920101,0.000044940633,0.00041571603,0.0001339214,0.005909426,0.0008082664,0.00084353564,0.0000074399827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000103302445,0.00021145816,0.91331893,0.0014592706,0.0003426359,0.000017170205,0.008244906,0.017600423,0.0059779645,0.01800013,0.00056338747,0.03416043],"study_design_scores_gemma":[0.00015720513,0.00009303963,0.006613585,0.001263569,0.000033750868,0.00004504166,0.0041072913,0.98499805,0.00010791043,0.0007642901,0.0016665529,0.00014973083],"about_ca_topic_score_codex":0.0047458448,"about_ca_topic_score_gemma":0.0023973407,"teacher_disagreement_score":0.96739763,"about_ca_system_score_codex":0.0008955383,"about_ca_system_score_gemma":0.0022625139,"threshold_uncertainty_score":0.99765474},"labels":[],"label_agreement":null},{"id":"W4402406519","doi":"10.23889/ijpds.v9i5.2851","title":"Evidence from an Applied Research Health Question (AHRQ): Physician-prescribed medications to children for oral health issues","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Education and Admissions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Family medicine","score_opus":0.39128207155291217,"score_gpt":0.6414510302899031,"score_spread":0.25016895873699097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406519","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04872944,0.0023361128,0.20277311,0.7347096,0.0062563824,0.002964286,0.0019671503,0.0001917044,0.000072228926],"genre_scores_gemma":[0.87277687,0.0007742886,0.09662814,0.01617151,0.004673437,0.00015252072,0.0080546,0.00003715138,0.0007314999],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99638486,0.000112645605,0.00060654717,0.0006559259,0.0018517732,0.00038825683],"domain_scores_gemma":[0.9965272,0.00035880343,0.0001661685,0.00055392424,0.0008667191,0.0015271745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0060769827,0.00011410556,0.00019996542,0.0006686657,0.00080418965,0.00050035835,0.0012897884,0.000041635478,0.00025415537],"category_scores_gemma":[0.006720801,0.00009487256,0.00004850941,0.00070227624,0.00015121645,0.0014758753,0.0001776785,0.00033994555,0.00003093487],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002900915,0.0004676595,0.002655107,0.00007141433,0.000105555875,0.0000017545643,0.0022714853,0.00015413754,0.003204796,0.028611299,0.34911013,0.6130566],"study_design_scores_gemma":[0.0022370885,0.0018527627,0.40511402,0.008523138,0.00010432164,0.00015069022,0.0017920292,0.18246928,0.0008478679,0.03166158,0.36462292,0.0006242958],"about_ca_topic_score_codex":0.0018189751,"about_ca_topic_score_gemma":0.00023693057,"teacher_disagreement_score":0.82404745,"about_ca_system_score_codex":0.0005452641,"about_ca_system_score_gemma":0.0042185583,"threshold_uncertainty_score":0.8045912},"labels":[],"label_agreement":null},{"id":"W4402406526","doi":"10.23889/ijpds.v9i5.2857","title":"Concurrent Opioid and Psychotropic Drug Use During Pregnancy: Descriptive Study from Two Canadian Provinces","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Prenatal Substance Exposure Effects","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; Manitoba Health","funders":"","keywords":"Drug; Opioid; Pregnancy; Medicine; Psychiatry; Internal medicine; Biology","score_opus":0.05324287628201882,"score_gpt":0.37191505545364534,"score_spread":0.3186721791716265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406526","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9910002,0.0015302035,0.00067045144,0.0005373423,0.004951081,0.00064610306,0.00061371096,0.000033301625,0.000017636521],"genre_scores_gemma":[0.9980084,0.000065847235,0.0010148934,0.000031850974,0.0004938781,0.000013187456,0.00024279025,0.000011409608,0.000117750875],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99828297,0.000029854225,0.0002835953,0.00047544218,0.00070788694,0.0002202535],"domain_scores_gemma":[0.99902,0.00009237725,0.00008963341,0.00025006416,0.0002565529,0.00029137832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032686468,0.00011502463,0.00012272272,0.0003775666,0.00025545002,0.0008403277,0.0005998989,0.000018425724,0.00002248226],"category_scores_gemma":[0.00047759208,0.00009467507,0.00002731224,0.00020501176,0.00010027586,0.0032761854,0.00013591938,0.0002089399,0.0000051133425],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000121499084,0.000097825796,0.9236727,0.000038292314,0.0001966947,0.00045487084,0.00313562,0.00002950381,0.0031501574,0.0011199779,0.0005228441,0.06746002],"study_design_scores_gemma":[0.0014519348,0.00012209959,0.97916466,0.0012526122,0.00006487686,0.0002368116,0.00029751533,0.014709029,0.00035025764,0.00058841123,0.0016012156,0.00016058485],"about_ca_topic_score_codex":0.0317376,"about_ca_topic_score_gemma":0.059801072,"teacher_disagreement_score":0.06729944,"about_ca_system_score_codex":0.00062922406,"about_ca_system_score_gemma":0.00050465873,"threshold_uncertainty_score":0.97471017},"labels":[],"label_agreement":null},{"id":"W4402406555","doi":"10.23889/ijpds.v9i5.2848","title":"Advancements in Pan-Canadian Data Access and Analysis Facilitation: Insights from Collaborative Health Research supported in Alberta, British Columbia, and Ontario","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Occupational Cancer Research Centre; Alberta Health; Ontario Institute for Cancer Research; Alberta Health Services","funders":"","keywords":"Facilitation; Data science; Political science; Computer science","score_opus":0.5723006984177732,"score_gpt":0.6344583978705374,"score_spread":0.06215769945276417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9856066,0.0005461032,0.00037636477,0.009810527,0.00049605744,0.0005644384,0.0024481018,0.000004311441,0.00014750616],"genre_scores_gemma":[0.9902053,0.0008673796,0.0023664257,0.0002847142,0.000073209,0.000011430009,0.0052662343,0.0000062004183,0.00091914175],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99628705,0.00014029778,0.0006708837,0.00082077,0.001773889,0.0003070918],"domain_scores_gemma":[0.99527526,0.0026311993,0.0000956368,0.00049207953,0.0011221609,0.00038364055],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007381845,0.000064436084,0.00021709764,0.0011883894,0.00031013618,0.0024817113,0.0013880959,0.00007856981,0.00017596077],"category_scores_gemma":[0.011792196,0.000079922036,0.000014751882,0.002059715,0.00035444705,0.0036934617,0.00081133674,0.0009628672,0.0000023256518],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005605874,0.00005286094,0.9725383,0.000023108933,0.00010424589,0.00012259865,0.00093120994,0.000023253828,0.000012022089,0.0006161655,0.000951311,0.024568867],"study_design_scores_gemma":[0.00061013846,0.00007422703,0.94212675,0.00041928657,0.000017022901,0.000020525407,0.00029737403,0.029046504,8.079693e-7,0.02025447,0.0070643765,0.00006851557],"about_ca_topic_score_codex":0.9702651,"about_ca_topic_score_gemma":0.999763,"teacher_disagreement_score":0.030411545,"about_ca_system_score_codex":0.0011937211,"about_ca_system_score_gemma":0.0058237235,"threshold_uncertainty_score":0.9998123},"labels":[],"label_agreement":null},{"id":"W4402406713","doi":"10.23889/ijpds.v9i5.2632","title":"A population-based repeated cross-sectional study using administrative health data to examine the impact of the COVID-19 pandemic on mental wellness in citizens of the Métis Nation of Ontario","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Mental health; Population; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Environmental health; 2019-20 coronavirus outbreak; Cross-sectional study; Geography; Economic growth; Psychology; Medicine; Psychiatry; Virology; Disease; Economics; Outbreak","score_opus":0.42152846419291806,"score_gpt":0.5704699572863283,"score_spread":0.14894149309341026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406713","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99141926,0.0000139580325,0.0003891433,0.0036535063,0.0018826342,0.0008230649,0.0017936653,0.0000056988374,0.000019079635],"genre_scores_gemma":[0.9992196,0.000003576367,0.00010430925,0.00031980046,0.00010593218,0.0000047675117,0.00017917086,0.000004765522,0.000058091136],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99684536,0.00031611088,0.0008212836,0.00029954128,0.0015105057,0.00020721003],"domain_scores_gemma":[0.9979647,0.0005900088,0.0005972446,0.0004545467,0.00028880598,0.0001047125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069439327,0.00008721529,0.00015120627,0.00023040324,0.0009146518,0.00021015725,0.002176617,0.000032995587,0.000054931304],"category_scores_gemma":[0.0030031619,0.000049475253,0.00007352966,0.0008008251,0.00024226568,0.0007637545,0.00029838222,0.00018946739,1.7729168e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008293845,0.00007959321,0.982173,0.000011735423,0.000018974546,3.221398e-7,0.0035111355,0.011685031,0.000026400137,0.002021405,0.00010220966,0.00028723816],"study_design_scores_gemma":[0.00031518986,0.000074815456,0.9849688,0.00011524378,0.0000055710484,0.000007643546,0.00077571016,0.012978819,0.0000073828073,0.0004283164,0.00027431233,0.00004824127],"about_ca_topic_score_codex":0.45057788,"about_ca_topic_score_gemma":0.3972262,"teacher_disagreement_score":0.05335165,"about_ca_system_score_codex":0.0029689928,"about_ca_system_score_gemma":0.0068284287,"threshold_uncertainty_score":0.99880195},"labels":[],"label_agreement":null},{"id":"W4402406719","doi":"10.23889/ijpds.v9i5.2612","title":"Mental health of children with special health needs in Manitoba, Canada","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child and Adolescent Health","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; McMaster University","funders":"","keywords":"Mental health; Environmental health; Psychology; Psychiatry; Medicine","score_opus":0.08232659607366132,"score_gpt":0.4424538111479106,"score_spread":0.3601272150742493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406719","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9253636,0.0005202183,0.0012469223,0.052208945,0.01541881,0.0014011015,0.0035931387,0.000029807827,0.0002174251],"genre_scores_gemma":[0.9933389,0.00020056375,0.00082226517,0.0020857507,0.0025313285,0.0000014826319,0.0009147945,0.000011847416,0.00009307256],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974954,0.000088485154,0.00077172177,0.00026186454,0.0009842988,0.00039820193],"domain_scores_gemma":[0.9989564,0.00006821687,0.00039026458,0.00020770653,0.00016819919,0.00020924037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019659502,0.00009515629,0.0001789985,0.0004844339,0.0006289356,0.000058928996,0.00089473015,0.000022348582,0.00006126424],"category_scores_gemma":[0.00009432254,0.000075146665,0.000020368792,0.0005093471,0.00006094704,0.0008870313,0.00016975285,0.0003938618,0.000002995227],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015208345,0.00009299258,0.82335865,0.0001241951,0.000035925765,0.0000042103457,0.002234465,0.0001471683,0.000016127215,0.013563934,0.10510106,0.055169195],"study_design_scores_gemma":[0.0009785665,0.00011088188,0.9560775,0.0014882805,0.0000023003042,0.00007056904,0.0019031727,0.0031235274,0.0000026780667,0.00029030623,0.035832524,0.000119694145],"about_ca_topic_score_codex":0.35299382,"about_ca_topic_score_gemma":0.7813075,"teacher_disagreement_score":0.42831367,"about_ca_system_score_codex":0.0019096744,"about_ca_system_score_gemma":0.008436418,"threshold_uncertainty_score":0.9971848},"labels":[],"label_agreement":null},{"id":"W4402406832","doi":"10.23889/ijpds.v9i5.2625","title":"New and Pre-existing Eating Disorders Among Adolescents and Young Adults During the COVID-19 Pandemic: A Population-Based Cohort Study","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Eating Disorders and Behaviors","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Women's College Hospital; Centre for Addiction and Mental Health; Hospital for Sick Children","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Cohort; Eating disorders; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Population; Cohort study; Medicine; Demography; Psychology; Pediatrics; Environmental health; Psychiatry; Virology; Disease; Outbreak; Internal medicine","score_opus":0.0550507887460319,"score_gpt":0.4192411181508618,"score_spread":0.36419032940482987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402406832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912384,0.00014137125,0.0056909565,0.00018902219,0.0019111398,0.0006658613,0.00007448895,0.00006160781,0.000027135173],"genre_scores_gemma":[0.99874866,0.000012371163,0.00057351845,0.00007418861,0.00023840052,0.000023637915,0.000119204626,0.000016612748,0.00019339382],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979944,0.000072586874,0.0004456837,0.00058108027,0.00066949014,0.00023672516],"domain_scores_gemma":[0.99904615,0.0001659342,0.00023856258,0.00027369134,0.00009626537,0.00017938543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014515464,0.00014297708,0.00011553687,0.00026998483,0.0009219856,0.0008356833,0.00072854216,0.00004106024,0.000041982028],"category_scores_gemma":[0.00075951085,0.00011050504,0.000032964657,0.000271537,0.00011080097,0.0009948467,0.00021141025,0.00024210778,0.0000011389119],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006634668,0.00004964646,0.98588926,0.000018628578,0.000026520045,0.000005171027,0.0012540984,0.00030330074,0.000015554133,0.00012296255,0.00006859769,0.012179913],"study_design_scores_gemma":[0.00078888773,0.000055419147,0.97590613,0.00016068327,0.000037371192,0.000084839914,0.0007102302,0.021764897,1.01899126e-7,0.00027078972,0.00008957127,0.00013107895],"about_ca_topic_score_codex":0.012875081,"about_ca_topic_score_gemma":0.00510632,"teacher_disagreement_score":0.021461595,"about_ca_system_score_codex":0.00015937758,"about_ca_system_score_gemma":0.00010163426,"threshold_uncertainty_score":0.99369824},"labels":[],"label_agreement":null},{"id":"W4403225780","doi":"10.23889/ijpds.v9i1.2380","title":"Validation of Preterm Birth Related Perinatal and Neonatal Data in the Canadian Discharge Abstract Database to Facilitate Long-term Outcomes Research of Individuals Born Preterm","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal and Neonatal Healthcare","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Manitoba Health; Mount Sinai Hospital; University of Manitoba","funders":"Agency for Healthcare Research and Quality; University of Manitoba","keywords":"Term (time); Medicine; Hospital discharge; Database; Computer science; Intensive care medicine","score_opus":0.3513024853924672,"score_gpt":0.5453078672796489,"score_spread":0.19400538188718164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403225780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9658494,0.00020299644,0.000110557834,0.003467483,0.0012789235,0.0008639859,0.0281515,0.000008981941,0.0000661634],"genre_scores_gemma":[0.9955123,0.000089200075,0.00043608376,0.00007966468,0.00009002604,0.000021326068,0.0035877572,0.000010870572,0.00017273625],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9963157,0.00024764912,0.0009402005,0.000517549,0.0015588229,0.00042006245],"domain_scores_gemma":[0.9973806,0.0007950126,0.00024531287,0.00080871774,0.00054065307,0.0002296961],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009582626,0.00012086664,0.00018085189,0.0010172965,0.00063853414,0.00018779919,0.0030488765,0.000078912555,0.00012119368],"category_scores_gemma":[0.0017569304,0.00008415333,0.000025742198,0.0005247074,0.00020520244,0.0030589472,0.0011042577,0.00067232107,0.000011833083],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009932298,0.000022892491,0.97171706,0.0005769237,0.00003148384,0.000038399125,0.0057104207,0.000011313257,0.00028524874,0.0028432857,0.00027571747,0.018387955],"study_design_scores_gemma":[0.00033129507,0.00006199628,0.99329466,0.0009663108,0.000006994975,0.00005501138,0.0005122685,0.0017351628,0.00007437712,0.00068409764,0.0021814478,0.00009640176],"about_ca_topic_score_codex":0.05783131,"about_ca_topic_score_gemma":0.0616475,"teacher_disagreement_score":0.029662926,"about_ca_system_score_codex":0.00023583534,"about_ca_system_score_gemma":0.00093741954,"threshold_uncertainty_score":0.955475},"labels":[],"label_agreement":null},{"id":"W4403283636","doi":"10.23889/ijpds.v9i5.2925","title":"IPDLN Workshop: Opportunities for Cross-Country Comparisons of Linked Administrative Education and Health Data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Legal Education and Practice Innovations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; University of Manitoba","funders":"","keywords":"Computer science; Data science; Business","score_opus":0.6097572420545042,"score_gpt":0.6301518757336448,"score_spread":0.020394633679140628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403283636","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05769012,0.0034585753,0.16056223,0.6932512,0.05607483,0.002966116,0.016375856,0.00021367648,0.009407396],"genre_scores_gemma":[0.97278345,0.00042949317,0.019259878,0.000800777,0.0013148111,0.000020004727,0.0035347089,0.000009187378,0.001847723],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982152,0.000052346553,0.00053711096,0.00033849152,0.0006748549,0.00018196876],"domain_scores_gemma":[0.9972635,0.0005437472,0.00043109598,0.000352557,0.0012615505,0.0001475474],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0052258754,0.000077217475,0.00011020646,0.00034803152,0.0010345321,0.0020401708,0.0016004698,0.00004251521,0.000051943774],"category_scores_gemma":[0.0032294462,0.00007524649,0.000021236123,0.00045184023,0.00046531204,0.008451267,0.0001825141,0.00019289904,0.0000011238718],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044723558,0.0001860087,0.005635922,0.000045984452,0.00005564289,5.3628344e-7,0.004116796,0.000029735802,0.000030378906,0.7369092,0.1460339,0.10691116],"study_design_scores_gemma":[0.0001583469,0.000034995308,0.011503168,0.00015625861,0.000018552146,0.000021509075,0.012402685,0.011177073,0.0000047475887,0.0062609566,0.95815015,0.00011153224],"about_ca_topic_score_codex":0.0014349199,"about_ca_topic_score_gemma":0.0016415982,"teacher_disagreement_score":0.9150933,"about_ca_system_score_codex":0.00019771094,"about_ca_system_score_gemma":0.008103829,"threshold_uncertainty_score":0.9989958},"labels":[],"label_agreement":null},{"id":"W4403398073","doi":"10.23889/ijpds.v9i1.2372","title":"Research data use in a digital society: a deliberative public engagement","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Guelph; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Deliberation; Public relations; Public engagement; Unintended consequences; Political science; Internet privacy; Business; Computer science; Politics","score_opus":0.9170635942163636,"score_gpt":0.7248893643938948,"score_spread":0.1921742298224688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403398073","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75832176,0.00084427645,0.070245765,0.15137798,0.008404165,0.0023088742,0.006321876,0.00016665387,0.0020086612],"genre_scores_gemma":[0.982553,0.00040784318,0.012783695,0.0003597788,0.0006942969,0.000011693439,0.001880157,0.000015829819,0.0012936927],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99378717,0.00007119064,0.0005998171,0.0008125757,0.004311706,0.00041751892],"domain_scores_gemma":[0.98766303,0.0072507015,0.000087512046,0.0013350113,0.0033500965,0.00031363606],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.029098444,0.00008615913,0.00012277853,0.0007513383,0.0003721939,0.004381093,0.0036545268,0.000088768924,0.000079810496],"category_scores_gemma":[0.06438355,0.00006969955,0.00005368205,0.001122994,0.00052659225,0.010206249,0.0033885771,0.0022030482,0.00003684534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064266735,0.0012361738,0.1841736,0.00025533338,0.0005796482,0.00069113425,0.0019339799,0.00020414351,0.001890152,0.44745496,0.115404576,0.24553363],"study_design_scores_gemma":[0.0014939565,0.00029658573,0.057011615,0.0013606348,0.00002076918,0.00035229954,0.0011719931,0.67400295,0.000043422187,0.1019099,0.16208877,0.00024710054],"about_ca_topic_score_codex":0.00013431555,"about_ca_topic_score_gemma":0.00037772433,"teacher_disagreement_score":0.6737988,"about_ca_system_score_codex":0.0006399186,"about_ca_system_score_gemma":0.002489734,"threshold_uncertainty_score":0.99974746},"labels":[{"model":"gemma","categories":["research_integrity"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":true,"confidence":"high"},{"model":"gpt","categories":["sts"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"split"},{"id":"W4403488559","doi":"10.23889/ijpds.v9i1.2412","title":"Creating an 11-year longitudinal substance use harm cohort from linked health and census data to analyse social drivers of health","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"HIV, Drug Use, Sexual Risk","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Saskatchewan; Saskatchewan Health Authority","funders":"Saskatchewan Health Research Foundation","keywords":"Census; Harm; Longitudinal data; Cohort; Substance use; Longitudinal study; Environmental health; Psychology; Demography; Medicine; Gerontology; Psychiatry; Social psychology; Sociology; Population","score_opus":0.3250137696684936,"score_gpt":0.5082723999104558,"score_spread":0.1832586302419622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403488559","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9775873,0.0001658766,0.009194054,0.005090244,0.000943616,0.0003401664,0.006635544,0.00003382983,0.000009372607],"genre_scores_gemma":[0.96449465,0.000121962556,0.027445499,0.00037182917,0.0005820454,0.0000018722131,0.0069219815,0.000016896953,0.00004325328],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99690175,0.000073948606,0.00074191904,0.000713398,0.0012642904,0.0003046685],"domain_scores_gemma":[0.9979244,0.00016627922,0.00038613647,0.0005819682,0.00049117894,0.000450022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027598678,0.00012981822,0.00030606097,0.00045065946,0.00043100643,0.0004253965,0.0011841741,0.00003494739,0.000020175885],"category_scores_gemma":[0.0012427273,0.00011923947,0.000031465515,0.0005132263,0.00014952302,0.0029891317,0.000346236,0.00021924458,0.000002740424],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019849921,0.000101500606,0.94561803,0.00004082648,0.00013657642,0.00002239254,0.0045642746,0.00013434955,0.0007003552,0.0011010864,0.0048015774,0.04258051],"study_design_scores_gemma":[0.00064795604,0.00019286678,0.9073092,0.00040131138,0.000056144105,0.00006786592,0.0034341728,0.08497943,0.000015508249,0.00016334676,0.0025938777,0.00013832531],"about_ca_topic_score_codex":0.0044626365,"about_ca_topic_score_gemma":0.0018136771,"teacher_disagreement_score":0.08484508,"about_ca_system_score_codex":0.0004354663,"about_ca_system_score_gemma":0.0008497737,"threshold_uncertainty_score":0.67462015},"labels":[],"label_agreement":null},{"id":"W4403950719","doi":"10.23889/ijpds.v9i5.2932","title":"Leveraging Full Count Census Data through Record Linkage","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadiana.org","funders":"","keywords":"Census; Record linkage; Computer science; Linkage (software); Count data; Data science; Statistics; Medicine; Population; Biology; Environmental health; Mathematics; Genetics","score_opus":0.5370824940918127,"score_gpt":0.5509539962253384,"score_spread":0.013871502133525615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403950719","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021364896,0.00043702207,0.9031435,0.024013445,0.03888318,0.00041520124,0.009441078,0.00013390621,0.002167734],"genre_scores_gemma":[0.8923285,0.00046338825,0.0896165,0.00245971,0.0033795638,0.000008620402,0.008766144,0.00003182752,0.0029457211],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99347734,0.0000912814,0.0010280062,0.0011620484,0.0039183185,0.00032301486],"domain_scores_gemma":[0.9957987,0.00080561236,0.0003590944,0.0021233286,0.00078048575,0.00013280002],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.015322757,0.00014118584,0.00016592885,0.0005475529,0.0005890452,0.006394272,0.013292665,0.000037351587,0.00028978518],"category_scores_gemma":[0.007141498,0.000108392305,0.000059133705,0.0009020839,0.00018437089,0.015421571,0.0038159594,0.00024934113,0.00021253298],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007716733,0.00007376689,0.0012414326,0.00001458058,0.00008035225,0.00007914997,0.00042342918,0.0006158901,0.00025945416,0.08077075,0.4325919,0.48377213],"study_design_scores_gemma":[0.00015505418,0.000020276433,0.0020466885,0.00007015387,0.000014367585,0.00009137753,0.00030670647,0.1741634,0.000009177234,0.055332158,0.76766115,0.0001294928],"about_ca_topic_score_codex":0.00036850246,"about_ca_topic_score_gemma":0.0001689752,"teacher_disagreement_score":0.87096363,"about_ca_system_score_codex":0.00020764838,"about_ca_system_score_gemma":0.00025974284,"threshold_uncertainty_score":0.99834925},"labels":[],"label_agreement":null},{"id":"W4404006113","doi":"10.23889/ijpds.v9i5.2936","title":"IPDLN Workshop: Opportunities for Cross-Country Comparisons of Linked Administrative Education and Health Data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Legal Education and Practice Innovations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; University of Manitoba","funders":"","keywords":"Computer science; Data science; Business","score_opus":0.6097572420545042,"score_gpt":0.6301518757336448,"score_spread":0.020394633679140628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404006113","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05769012,0.0034585753,0.16056223,0.6932512,0.05607483,0.002966116,0.016375856,0.00021367648,0.009407396],"genre_scores_gemma":[0.97278345,0.00042949317,0.019259878,0.000800777,0.0013148111,0.000020004727,0.0035347089,0.000009187378,0.001847723],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982152,0.000052346553,0.00053711096,0.00033849152,0.0006748549,0.00018196876],"domain_scores_gemma":[0.9972635,0.0005437472,0.00043109598,0.000352557,0.0012615505,0.0001475474],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0052258754,0.000077217475,0.00011020646,0.00034803152,0.0010345321,0.0020401708,0.0016004698,0.00004251521,0.000051943774],"category_scores_gemma":[0.0032294462,0.00007524649,0.000021236123,0.00045184023,0.00046531204,0.008451267,0.0001825141,0.00019289904,0.0000011238718],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044723558,0.0001860087,0.005635922,0.000045984452,0.00005564289,5.3628344e-7,0.004116796,0.000029735802,0.000030378906,0.7369092,0.1460339,0.10691116],"study_design_scores_gemma":[0.0001583469,0.000034995308,0.011503168,0.00015625861,0.000018552146,0.000021509075,0.012402685,0.011177073,0.0000047475887,0.0062609566,0.95815015,0.00011153224],"about_ca_topic_score_codex":0.0014349199,"about_ca_topic_score_gemma":0.0016415982,"teacher_disagreement_score":0.9150933,"about_ca_system_score_codex":0.00019771094,"about_ca_system_score_gemma":0.008103829,"threshold_uncertainty_score":0.9989958},"labels":[],"label_agreement":null},{"id":"W4404144912","doi":"10.23889/ijpds.v9i5.2940","title":"Constantly changing, constantly adapting: Lives and life-course data of children and childhood social care","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Intergenerational Family Dynamics and Caregiving","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; First Nations Health and Social Secretariat of Manitoba","funders":"","keywords":"Life course approach; Course (navigation); Psychology; Computer science; Developmental psychology; Data science; Engineering","score_opus":0.03856674186093836,"score_gpt":0.37506914200242686,"score_spread":0.3365024001414885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404144912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97443324,0.004365221,0.0056662955,0.0031467173,0.0041701007,0.00039536878,0.0067572654,0.000051213057,0.0010145609],"genre_scores_gemma":[0.9962139,0.0003997171,0.0015631947,0.00010219553,0.0009037013,0.0000014785269,0.00075377396,0.000008589768,0.000053414282],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99820864,0.00004359496,0.0003131427,0.00040564756,0.00081017416,0.00021880848],"domain_scores_gemma":[0.9989272,0.00011856763,0.00017622559,0.00018572509,0.00047623686,0.000116063246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016315458,0.00009496494,0.00011693046,0.0002821846,0.0010242761,0.0008759448,0.0012652527,0.00004021049,0.000019350306],"category_scores_gemma":[0.00066713174,0.000090807516,0.000028357148,0.00024879538,0.0005868425,0.0022528495,0.00059404195,0.00012576947,5.9830353e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046006982,0.00007757524,0.06313741,0.000035425302,0.0003302451,0.000013652554,0.035203516,0.000089531124,0.0004303929,0.8100315,0.0026096518,0.08799512],"study_design_scores_gemma":[0.002586597,0.00030549223,0.5862787,0.0016666979,0.0005955155,0.0005730041,0.11105533,0.24847715,0.00008176084,0.015854606,0.030779362,0.0017458466],"about_ca_topic_score_codex":0.00039544248,"about_ca_topic_score_gemma":0.00087805046,"teacher_disagreement_score":0.7941769,"about_ca_system_score_codex":0.00006419095,"about_ca_system_score_gemma":0.00073598215,"threshold_uncertainty_score":0.8446756},"labels":[],"label_agreement":null},{"id":"W4404190095","doi":"10.23889/ijpds.v9i5.2941","title":"Turning Research Ideas into Reality: A Guide to Developing a Simulated Research Protocol using Administrative Data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Protocol (science); Computer science; Data science; Medicine","score_opus":0.8223408008841603,"score_gpt":0.7532386221673946,"score_spread":0.06910217871676572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404190095","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15531817,0.00023647683,0.2162202,0.46921042,0.017955106,0.11534526,0.0028621883,0.0006363363,0.022215845],"genre_scores_gemma":[0.9414971,0.000031006937,0.053217445,0.00040551866,0.0032153055,0.00051768357,0.00031062114,0.000032659736,0.0007726891],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9920885,0.0007235755,0.00064563437,0.0008101958,0.005003094,0.0007290265],"domain_scores_gemma":[0.98996633,0.0018170885,0.00014472994,0.00069702324,0.0069430876,0.00043174467],"candidate_categories":["metaresearch","sts","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.05885621,0.00011348863,0.00014009168,0.0011341784,0.004770993,0.006910331,0.0061819516,0.00011578205,0.00004177385],"category_scores_gemma":[0.0533498,0.00010564883,0.000033722394,0.0025652908,0.0008769681,0.008034828,0.0023066394,0.00095848594,0.00001883459],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004135594,0.00014789958,0.0024016367,0.00011210879,0.00020657887,0.00019693389,0.052366972,0.0028703783,0.00535281,0.81282187,0.059211273,0.06389797],"study_design_scores_gemma":[0.0002912484,0.00011500285,0.0012598283,0.001053011,0.000009067317,0.00002349373,0.0074988226,0.12452772,0.000094480805,0.18098666,0.6838548,0.0002858507],"about_ca_topic_score_codex":0.020660117,"about_ca_topic_score_gemma":0.007880912,"teacher_disagreement_score":0.7861789,"about_ca_system_score_codex":0.0018175395,"about_ca_system_score_gemma":0.0085638305,"threshold_uncertainty_score":0.9991951},"labels":[],"label_agreement":null},{"id":"W4404528517","doi":"10.23889/ijpds.v9i1.2407","title":"Secondary use of routinely collected administrative health data for epidemiologic research: Answering research questions using data collected for a different purpose","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; Simon Fraser University; AIDS Vancouver","funders":"","keywords":"Data science; Computer science","score_opus":0.9660910023644246,"score_gpt":0.746661212221578,"score_spread":0.21942979014284658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404528517","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.112683505,0.00057210884,0.75078726,0.024677446,0.00889396,0.008614871,0.09353854,0.00013836389,0.00009393619],"genre_scores_gemma":[0.7960751,0.000564425,0.14364006,0.0007107657,0.0022003595,0.00034257374,0.055484813,0.000051002255,0.0009309087],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9934256,0.0011666628,0.0020449318,0.00081757206,0.0016287422,0.00091647834],"domain_scores_gemma":[0.97868365,0.014023745,0.00081125344,0.0015253285,0.00450219,0.00045380645],"candidate_categories":["metaresearch","sts"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.042351037,0.0001497497,0.00038388098,0.0012838625,0.0043766424,0.00037873478,0.0039275675,0.00014308371,0.000056953508],"category_scores_gemma":[0.069462255,0.00012033229,0.0000425725,0.0013355716,0.00038003232,0.0041501955,0.0018978945,0.0012584038,0.000003130855],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003446424,0.0005388604,0.010636159,0.0046984893,0.0003297201,0.0000104613555,0.0052444306,0.00094033877,0.0016417409,0.09661145,0.81137466,0.064527296],"study_design_scores_gemma":[0.00076878245,0.00036020915,0.010702267,0.0019007352,0.000015831696,0.000021686,0.0007774686,0.8665441,0.00000746509,0.00529416,0.113493,0.000114272996],"about_ca_topic_score_codex":0.00146288,"about_ca_topic_score_gemma":0.0016142693,"teacher_disagreement_score":0.8656038,"about_ca_system_score_codex":0.0011259734,"about_ca_system_score_gemma":0.009368939,"threshold_uncertainty_score":0.9969195},"labels":[{"model":"gemma","categories":["metaresearch"],"domain":"methods","study_design":"theoretical_or_conceptual","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"medium"}],"label_agreement":"split"},{"id":"W4405242436","doi":"10.23889/ijpds.v9i2.2458","title":"Neonates With In-Utero SSRI Exposure (NeoWISE): a retrospective cohort study examining the effect of newborn feeding method on newborn withdrawal","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Maternal Mental Health During Pregnancy and Postpartum","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Kingston Health Sciences Centre; Ottawa Hospital; Centre for Excellence in Mining Innovation; University of Toronto; Agricultural Research Institute of Ontario; Ontario Stroke Network; Queen's University","funders":"Canadian Institutes of Health Research","keywords":"Retrospective cohort study; Medicine; In utero; Cohort; Pediatrics; Fetus; Pregnancy; Internal medicine; Biology","score_opus":0.03169711833532642,"score_gpt":0.3973626040171245,"score_spread":0.3656654856817981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405242436","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99300265,0.00014423829,0.0032777288,0.000641466,0.001672175,0.0009737696,0.00007340556,0.000023212819,0.00019137403],"genre_scores_gemma":[0.9955118,0.000016479325,0.003906343,0.00007224994,0.00030346666,0.0000348845,0.0000472969,0.000015136365,0.00009236927],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975627,0.00010187656,0.00045711073,0.00043496297,0.0012155196,0.00022784549],"domain_scores_gemma":[0.9987627,0.00040573705,0.00021437882,0.00032123446,0.00020006171,0.0000958545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034682692,0.00014908938,0.00025036218,0.00039751542,0.00023030865,0.00023557841,0.0006969019,0.000031147505,0.000019060139],"category_scores_gemma":[0.00039144658,0.000086186425,0.000035275512,0.00041050604,0.00008812194,0.00087885483,0.00014496628,0.0003568809,0.0000022701513],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012646395,0.000057146754,0.9776872,0.00011065913,0.00008320608,0.00010926305,0.0004745165,0.00021588065,0.0001647937,0.0004112784,0.000017584209,0.019403834],"study_design_scores_gemma":[0.0012687161,0.0029003925,0.98245025,0.0032763095,0.0000661781,0.00056666177,0.00013499202,0.008126202,0.00076715456,0.00013121402,0.00022780492,0.00008415242],"about_ca_topic_score_codex":0.00027704818,"about_ca_topic_score_gemma":0.000059054804,"teacher_disagreement_score":0.019319681,"about_ca_system_score_codex":0.00030558708,"about_ca_system_score_gemma":0.0001318083,"threshold_uncertainty_score":0.35145804},"labels":[],"label_agreement":null},{"id":"W4406906379","doi":"10.23889/ijpds.v10i2.2466","title":"Minimum elements for reporting a feasibility assessment of algorithms based on routinely collected health data for multi-jurisdiction use: Health Data Research Network Canada recommendations","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"George & Fay Yee Centre for Healthcare Innovation; University of British Columbia; Public Health Agency of Canada; University of Manitoba","funders":"","keywords":"Observational study; Jurisdiction; Computer science; Unavailability; Transparency (behavior); Strengthening the reporting of observational studies in epidemiology; Data mining; Algorithm; Medicine; Data science; Engineering; Computer security; Reliability engineering; Pathology","score_opus":0.8388616523280394,"score_gpt":0.6946497670255899,"score_spread":0.14421188530244955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406906379","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015394385,0.000034136778,0.9071584,0.05035099,0.0076758233,0.0047332174,0.02843505,0.000031573367,0.0000414148],"genre_scores_gemma":[0.19145842,0.00013349102,0.6745353,0.008102409,0.0010492343,0.00031806287,0.12383044,0.000028295164,0.00054436654],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99149656,0.00063707406,0.0044239373,0.0008049537,0.0017489524,0.00088850316],"domain_scores_gemma":[0.9860335,0.0032173838,0.0051655243,0.0018519012,0.0033860842,0.0003456079],"candidate_categories":["metaresearch","sts"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.060193438,0.0001453158,0.00039992813,0.00053447805,0.0051334705,0.00015038393,0.0029496027,0.00008281921,0.000026688513],"category_scores_gemma":[0.036489155,0.00013451962,0.00003514475,0.0009306983,0.00008255937,0.001819135,0.0009996638,0.00065410766,3.1238937e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054003444,0.000315292,0.15147957,0.0006891019,0.000065866,3.5765032e-7,0.00015152212,0.0021689557,0.000005512713,0.00273631,0.8009942,0.040853243],"study_design_scores_gemma":[0.0018328833,0.00016559492,0.093253076,0.0008985953,0.000009256111,0.0000011618646,0.00026708923,0.81067353,4.739221e-7,0.00022934261,0.09259369,0.00007530054],"about_ca_topic_score_codex":0.08226736,"about_ca_topic_score_gemma":0.19608724,"teacher_disagreement_score":0.8085046,"about_ca_system_score_codex":0.003210871,"about_ca_system_score_gemma":0.028104292,"threshold_uncertainty_score":0.9961617},"labels":[],"label_agreement":null},{"id":"W4407529813","doi":"10.23889/ijpds.v10i1.2475","title":"Kids' Environment and Health Cohort: Database Protocol","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"Economic and Social Research Council; Medical Research Council","keywords":"Protocol (science); Database; Cohort; Computer science; Medicine; Environmental health; Internal medicine","score_opus":0.06210322717265559,"score_gpt":0.42761986176677513,"score_spread":0.36551663459411954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407529813","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2394388,0.00011588549,0.5622844,0.058653276,0.00531595,0.12410806,0.0022439705,0.00017776493,0.007661864],"genre_scores_gemma":[0.9109318,0.00029883615,0.068441875,0.009587309,0.00042556805,0.00804353,0.00090650044,0.000039822833,0.0013247362],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99737805,0.000060317543,0.00049079995,0.00074887456,0.0009801337,0.00034183983],"domain_scores_gemma":[0.99883246,0.00006494105,0.00030646173,0.000539045,0.000023864699,0.00023323565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003981903,0.00013086428,0.00012450297,0.00017996063,0.0007278152,0.00024476968,0.0013016313,0.000028034754,0.00040028855],"category_scores_gemma":[0.000350636,0.00012211109,0.000022355785,0.0001942004,0.00036365632,0.0023826137,0.0012756849,0.00019039662,0.000047887428],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005692107,0.0001580428,0.7882329,0.000021627833,0.000027789825,0.0000064601218,0.00010385628,0.001035189,0.0016836633,0.0019973558,0.007835534,0.19884063],"study_design_scores_gemma":[0.00075791765,0.000053264663,0.8101411,0.000084921,0.000009205888,0.000043377273,0.00005339688,0.025011813,0.00016821138,0.0018601456,0.16164199,0.00017468339],"about_ca_topic_score_codex":0.0005602384,"about_ca_topic_score_gemma":0.00008102221,"teacher_disagreement_score":0.671493,"about_ca_system_score_codex":0.00084678316,"about_ca_system_score_gemma":0.00012723009,"threshold_uncertainty_score":0.559784},"labels":[],"label_agreement":null},{"id":"W4407991816","doi":"10.23889/ijpds.v9i2.2459","title":"Early child development in England: Cross-sectional analysis of ASQ®-3 records from the 2-2½-year universal health visiting review using national administrative data (Community Service Dataset, CSDS)","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute for Health and Care Research","keywords":"Medicine; Child development; Quarter (Canadian coin); Family medicine; Pediatrics; Geography; Psychiatry","score_opus":0.2687821797572317,"score_gpt":0.5341172938036338,"score_spread":0.26533511404640214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407991816","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94229716,0.0006096454,0.004638054,0.019984381,0.0024129322,0.00064527476,0.028953696,0.000018130499,0.00044070074],"genre_scores_gemma":[0.9745102,0.00057680835,0.00519609,0.003576301,0.0002763405,0.0000032150915,0.015835686,0.000004420783,0.000020941843],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967246,0.00045471202,0.00086757826,0.0003308524,0.0013604838,0.00026176914],"domain_scores_gemma":[0.9968727,0.000966762,0.0006548076,0.00048090264,0.00091662875,0.00010817231],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.011693881,0.00009597014,0.00022575555,0.00037791676,0.002164943,0.00039918305,0.0036785621,0.00004168405,0.00008899476],"category_scores_gemma":[0.0035339678,0.0000836108,0.000039908035,0.0015374945,0.00018026182,0.0024673683,0.0007674061,0.0003465997,0.0000010215423],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005202558,0.00006693996,0.9880989,0.00004694985,0.00019015663,6.6489554e-7,0.0012873186,0.0005634497,9.898259e-7,0.0071945256,0.00056526874,0.0019327684],"study_design_scores_gemma":[0.0002970225,0.00000610177,0.96506006,0.0005263401,0.0000326912,0.0000013367139,0.0006521284,0.0066229957,5.699511e-7,0.00034655063,0.026378509,0.000075691365],"about_ca_topic_score_codex":0.09042586,"about_ca_topic_score_gemma":0.116688676,"teacher_disagreement_score":0.03221301,"about_ca_system_score_codex":0.0008046491,"about_ca_system_score_gemma":0.0039239586,"threshold_uncertainty_score":0.9991341},"labels":[],"label_agreement":null},{"id":"W4408192777","doi":"10.23889/ijpds.v10i1.2496","title":"Cohort Profile Update: Reflecting back and looking ahead: Updating the Comparative Outcomes and Service Utilization Trends (COAST) Study to include 28 years of linked data from people with and without HIV in British Columbia, Canada","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"HIV/AIDS Research and Interventions","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; Simon Fraser University; AIDS Vancouver","funders":"National Institute on Drug Abuse","keywords":"Cohort; Human immunodeficiency virus (HIV); Service (business); Cohort study; Medicine; Business; Marketing; Family medicine; Internal medicine","score_opus":0.10144139604064333,"score_gpt":0.445731293242084,"score_spread":0.34428989720144065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408192777","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99608624,0.000032328207,0.001074515,0.0013550443,0.000070901755,0.0004499146,0.0008700291,0.0000035586797,0.000057468173],"genre_scores_gemma":[0.99571806,0.000013647851,0.0027001612,0.00016758122,0.00002576366,0.000008035811,0.0010572701,0.00000452906,0.0003049407],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985504,0.00005876943,0.0003711919,0.00033336598,0.0005483985,0.00013783977],"domain_scores_gemma":[0.99896705,0.00012375637,0.00016311636,0.00026620872,0.00039281088,0.00008706142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010604435,0.000058019396,0.00018403676,0.00017318106,0.00025785307,0.00043498538,0.0005306994,0.000013242243,0.000034454744],"category_scores_gemma":[0.0006691515,0.000058202553,0.000006550157,0.00051278615,0.00006338529,0.00087716244,0.00069940265,0.00014701876,1.8537017e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000538652,0.000056449884,0.98912746,0.000010260574,0.000061986946,0.000002044817,0.00042090172,0.000020572508,0.00005360546,0.000008840416,0.0016982296,0.00848581],"study_design_scores_gemma":[0.0009911752,0.00010399375,0.9394609,0.00032746713,0.00003100312,0.000026348198,0.0029221568,0.05581176,0.000004363673,0.000027363865,0.00024322895,0.000050270963],"about_ca_topic_score_codex":0.5640408,"about_ca_topic_score_gemma":0.98394847,"teacher_disagreement_score":0.4199077,"about_ca_system_score_codex":0.00010292891,"about_ca_system_score_gemma":0.0003246971,"threshold_uncertainty_score":0.4388623},"labels":[],"label_agreement":null},{"id":"W4411181559","doi":"10.23889/ijpds.v10i2.2926","title":"Development and Validation of a Mortality Risk Prediction Index Score for Adults Living with HIV and Multiple Chronic Comorbidities","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"HIV-related health complications and treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"AIDS Vancouver; University of British Columbia","funders":"Ministry of Health, British Columbia","keywords":"Medicine; Population; Comorbidity; Statistic; Human immunodeficiency virus (HIV); Framingham Risk Score; Disease; Gerontology; Internal medicine; Demography; Environmental health; Statistics; Family medicine","score_opus":0.05525889375274938,"score_gpt":0.3776947017838802,"score_spread":0.3224358080311308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411181559","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9460504,0.00008618165,0.052606013,0.00022703547,0.00018160777,0.00045136,0.00036809858,0.000009538581,0.000019750973],"genre_scores_gemma":[0.98769057,0.000093300296,0.01154822,0.000017383441,0.000047518166,0.000022726219,0.0005350596,0.000003688175,0.00004151069],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990659,0.000010132386,0.00032613167,0.00021239147,0.0002850845,0.00010039057],"domain_scores_gemma":[0.9989116,0.00011817058,0.00025962747,0.00014727934,0.00050049584,0.000062836065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005652614,0.00006267476,0.000096900454,0.00023598042,0.00036026226,0.00005754718,0.00014251658,0.000025685082,0.000002514432],"category_scores_gemma":[0.0004173096,0.0000503805,0.000011214837,0.00012882888,0.000088091765,0.0005793489,0.00007011845,0.00006657483,1.4987985e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000114919465,0.000059438946,0.9854936,0.000069053596,0.00006949216,2.4602636e-7,0.00022813924,0.00021414807,0.00005884621,0.0005006222,0.00005689034,0.01313461],"study_design_scores_gemma":[0.0013875857,0.00008875721,0.8864413,0.0007297502,0.000052285603,0.000026554582,0.00011592737,0.1102728,0.00017342696,0.00017491162,0.0005000477,0.000036687103],"about_ca_topic_score_codex":0.00012241064,"about_ca_topic_score_gemma":0.00012762782,"teacher_disagreement_score":0.11005865,"about_ca_system_score_codex":0.0001892756,"about_ca_system_score_gemma":0.00035355473,"threshold_uncertainty_score":0.27708825},"labels":[],"label_agreement":null},{"id":"W4411607411","doi":"10.23889/ijpds.v10i2.2961","title":"Characterising firearm-related databases across Canada: opportunities for data linkage to inform understanding of injury burden and prevention","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Gun Ownership and Violence Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hospital for Sick Children; University of Toronto; St. Michael's Hospital; Institute for Clinical Evaluative Sciences","funders":"Hospital for Sick Children","keywords":"Linkage (software); Record linkage; Database; Data science; Computer science; Environmental health; Medicine; Chemistry; Gene","score_opus":0.4333360846196065,"score_gpt":0.5330922443425896,"score_spread":0.09975615972298313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411607411","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8618818,0.00011115073,0.08939158,0.032225262,0.004232479,0.0011965217,0.010496115,0.00002870106,0.00043636683],"genre_scores_gemma":[0.9963536,0.00020115271,0.0014755898,0.000091804155,0.00017969067,0.0000050216913,0.0011263364,0.0000038839707,0.000562876],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982193,0.000037790945,0.0003841808,0.00025938396,0.0008324164,0.0002669244],"domain_scores_gemma":[0.9986011,0.0002401627,0.00022065474,0.0003095439,0.0004981723,0.00013037704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004277959,0.00006524868,0.00010547811,0.00019266338,0.0011657845,0.00042836217,0.0017986095,0.000028647675,0.000014737729],"category_scores_gemma":[0.0028355927,0.0000620125,0.00001676439,0.00035281942,0.0002363909,0.0034776514,0.0007268073,0.000090794056,1.5732523e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046385592,0.0000585676,0.052051544,0.00014379539,0.00019353558,0.0000070405645,0.0055473396,0.00012844459,0.0020514058,0.17713842,0.0060754153,0.75614065],"study_design_scores_gemma":[0.0025594379,0.00028730696,0.13074957,0.0036392866,0.0001275724,0.000028119099,0.11073641,0.08777621,0.00068863155,0.027124777,0.6353458,0.00093687075],"about_ca_topic_score_codex":0.10149949,"about_ca_topic_score_gemma":0.16366546,"teacher_disagreement_score":0.7552038,"about_ca_system_score_codex":0.00034322834,"about_ca_system_score_gemma":0.0015541082,"threshold_uncertainty_score":0.9044837},"labels":[],"label_agreement":null},{"id":"W4413774427","doi":"10.23889/ijpds.v10i4.3246","title":"Public trust, literacy and health data foundations in Canada","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; Memorial University of Newfoundland","funders":"","keywords":"Literacy; Health literacy; Public health; Public trust; Political science; Public relations; Data science; Psychology; Environmental health; Computer science; Medicine; Pedagogy; Nursing; Health care; Law","score_opus":0.3182799121721329,"score_gpt":0.5711104753177529,"score_spread":0.25283056314562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413774427","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08276756,0.0012104909,0.02533702,0.8510504,0.026909918,0.0018095238,0.0056815534,0.000056227538,0.0051773316],"genre_scores_gemma":[0.9492927,0.0005462996,0.0074098264,0.037380658,0.00045397854,0.00002217727,0.0039575547,0.000009161533,0.00092762976],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976871,0.00010302096,0.0008396311,0.00040243217,0.0005639692,0.0004038165],"domain_scores_gemma":[0.9979174,0.00038142598,0.00037438958,0.0006894499,0.00045936953,0.00017796356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036163973,0.00008399065,0.00016620786,0.0005280974,0.001293479,0.0001896534,0.0024401436,0.000029264564,0.00008689675],"category_scores_gemma":[0.0014820715,0.000076691926,0.000010273783,0.0004887391,0.000051594074,0.0040578283,0.0012487003,0.00035635816,0.0000028315008],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017122284,0.00001695295,0.79683256,0.000037456863,0.000011341937,0.0000021405822,0.00010683512,0.000008312332,0.0000020214027,0.02995469,0.0856851,0.08732546],"study_design_scores_gemma":[0.0005256285,0.0000065693193,0.63567495,0.00008763228,0.0000027720303,0.0000067469537,0.00016293312,0.013639891,1.1155629e-7,0.004073398,0.34575945,0.00005992343],"about_ca_topic_score_codex":0.6119331,"about_ca_topic_score_gemma":0.8888345,"teacher_disagreement_score":0.8665252,"about_ca_system_score_codex":0.0031743618,"about_ca_system_score_gemma":0.02787338,"threshold_uncertainty_score":0.99485254},"labels":[],"label_agreement":null},{"id":"W4413775356","doi":"10.23889/ijpds.v10i4.3114","title":"Developing a Health Data Analytic Service to Serve the Private Sector for Public Benefit","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University Health Network; University of British Columbia; University of New Brunswick","funders":"","keywords":"Private sector; Public sector; Business; Service (business); Public relations; Marketing; Economics; Economic growth; Political science","score_opus":0.588304350646068,"score_gpt":0.6075084979088123,"score_spread":0.01920414726274433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413775356","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12931813,0.00012107228,0.34324118,0.50826216,0.012132396,0.0033464916,0.003442134,0.000075845644,0.000060602644],"genre_scores_gemma":[0.8597978,0.000094591225,0.06250713,0.07092306,0.0020839733,0.0002550145,0.0036753367,0.000039641633,0.0006235054],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963339,0.00014056302,0.0012646121,0.00069782673,0.0008719609,0.0006911499],"domain_scores_gemma":[0.9935897,0.0010898656,0.0006932507,0.0014362991,0.0029410005,0.00024987216],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0077755456,0.00014850362,0.0002161004,0.00053637946,0.003754458,0.0003720278,0.007594486,0.00006897267,0.000049285434],"category_scores_gemma":[0.0055085625,0.000113312155,0.000036795343,0.0014025959,0.00006526909,0.0024673822,0.0023538654,0.00039551384,0.00003371361],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040164508,0.00010028942,0.30020756,0.0005215986,0.00022062978,0.0000020393272,0.0040579266,0.0023025565,0.00014989714,0.52406037,0.04179099,0.12618452],"study_design_scores_gemma":[0.0004293968,0.000068735746,0.09586375,0.0010730083,0.000027791682,0.00001240027,0.0025346377,0.38182062,0.000028738192,0.041268434,0.4765835,0.00028897033],"about_ca_topic_score_codex":0.0040258644,"about_ca_topic_score_gemma":0.035919398,"teacher_disagreement_score":0.7304796,"about_ca_system_score_codex":0.0012405987,"about_ca_system_score_gemma":0.0031534852,"threshold_uncertainty_score":0.9977749},"labels":[],"label_agreement":null},{"id":"W4413775409","doi":"10.23889/ijpds.v10i4.3155","title":"The Kids’ Environment and Health Cohort: a novel administrative data resource for research on the environmental determinants of child health in England","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Child health; Resource (disambiguation); Health data; Environmental health; Environmental data; Business; Environmental resource management; Environmental planning; Medicine; Political science; Computer science; Geography; Environmental science; Economic growth; Pediatrics; Health care; Economics","score_opus":0.38116155500697385,"score_gpt":0.5228636901232881,"score_spread":0.1417021351163143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413775409","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7619342,0.0005469141,0.0016933839,0.22414833,0.0008432029,0.0036545657,0.0069067157,0.0000072927423,0.00026539204],"genre_scores_gemma":[0.99566936,0.001198937,0.0006525819,0.0019181923,0.00009007049,0.000029765792,0.00035607157,0.000006394469,0.00007862263],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99774784,0.000097426375,0.00051950366,0.0004338903,0.00081443693,0.00038687527],"domain_scores_gemma":[0.9981971,0.00068688975,0.00034093176,0.00062658894,0.000014329996,0.00013418692],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.011057167,0.00008901913,0.00013019,0.0001279549,0.0013860917,0.00015303277,0.002028344,0.000023583214,0.000021211641],"category_scores_gemma":[0.0006007192,0.00005642997,0.000015138576,0.00017116265,0.00053160836,0.0005340377,0.0010791229,0.0002152169,0.0000018975891],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00077455473,0.0006191018,0.6631916,0.000040538336,0.000033107895,0.000001930623,0.0019913286,0.0005204308,0.0003012303,0.004754034,0.029872619,0.2978995],"study_design_scores_gemma":[0.0007521517,0.00030402048,0.8509249,0.00019912542,0.0000028949548,0.000022943568,0.00053151767,0.024551218,0.000044892022,0.0011044104,0.121488504,0.000073415344],"about_ca_topic_score_codex":0.00043960937,"about_ca_topic_score_gemma":0.0018031443,"teacher_disagreement_score":0.2978261,"about_ca_system_score_codex":0.0005866943,"about_ca_system_score_gemma":0.00013726344,"threshold_uncertainty_score":0.999914},"labels":[],"label_agreement":null},{"id":"W4413783546","doi":"10.23889/ijpds.v10i4.3284","title":"A study of occupational employment and retention using linked occupational licensing, education and population registry data","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Business; Population; Environmental health; Medicine","score_opus":0.1726670310036161,"score_gpt":0.4547795320056041,"score_spread":0.28211250100198804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413783546","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73808426,0.00010357088,0.25842074,0.0004228059,0.0025698708,0.00028214126,0.00007979233,0.00001799689,0.000018832172],"genre_scores_gemma":[0.90740615,0.000023152756,0.09165469,0.00006991673,0.00018590983,0.000004574529,0.0006098722,0.0000051775382,0.000040559356],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99787533,0.000035717996,0.00057718914,0.0005730775,0.0007931722,0.00014550674],"domain_scores_gemma":[0.9977868,0.00011846615,0.00042327645,0.000740722,0.00084555655,0.00008516221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012968325,0.000119742035,0.00013232019,0.00063368626,0.00041531184,0.0005778215,0.0017921523,0.000040673203,0.0000019290742],"category_scores_gemma":[0.00077506376,0.00012321817,0.000016987236,0.00046496297,0.000061208906,0.003821227,0.0010164821,0.0001097984,1.9278079e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013285792,0.0009923828,0.77981913,0.000058995465,0.00016299471,0.0000019895963,0.0007565953,0.015543209,0.0017909656,0.13516928,0.0009969362,0.064574644],"study_design_scores_gemma":[0.0003114794,0.000028810156,0.62505794,0.000091795264,0.000021501091,0.0000456296,0.00013379917,0.37209907,0.000007061123,0.0018699476,0.00024437002,0.000088635265],"about_ca_topic_score_codex":0.0005539402,"about_ca_topic_score_gemma":0.00009026287,"teacher_disagreement_score":0.35655585,"about_ca_system_score_codex":0.00016788021,"about_ca_system_score_gemma":0.0006401799,"threshold_uncertainty_score":0.55719465},"labels":[],"label_agreement":null},{"id":"W4413790875","doi":"10.23889/ijpds.v10i4.3209","title":"Investigating data challenges and service use patterns in mental health care for children and young people in England","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Child and Adolescent Health","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Mental health; Service (business); Mental healthcare; Psychology; Data science; Psychiatry; Computer science; Business; Marketing","score_opus":0.1381757826962513,"score_gpt":0.47258245348387196,"score_spread":0.33440667078762065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413790875","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97187835,0.00083668844,0.0003207384,0.022066342,0.0011795345,0.00088693463,0.0028167027,0.0000089967,0.000005731525],"genre_scores_gemma":[0.99085236,0.0018694423,0.0020108707,0.0018200766,0.00022836731,0.000004610746,0.0031977636,0.0000066032226,0.000009895928],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984228,0.00009658199,0.0005108233,0.00042660456,0.00026913488,0.00027405328],"domain_scores_gemma":[0.99899685,0.00020115664,0.00024506234,0.00028172813,0.00016581904,0.00010935654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019091868,0.00008702773,0.00015276771,0.0003299175,0.0006564842,0.000099773795,0.0007767751,0.000039149243,0.0000016922172],"category_scores_gemma":[0.0007168069,0.00008064001,0.0000069420435,0.00016110626,0.00002970729,0.0018063479,0.0007665191,0.00026037925,1.8838635e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025708167,0.000020606481,0.967347,0.00013040194,0.000004319169,1.2985281e-7,0.009958152,0.00000714292,0.0000079673055,0.0010861977,0.00019515598,0.021217166],"study_design_scores_gemma":[0.0017303099,0.000016984359,0.98268527,0.001052776,0.0000024809558,0.000009189485,0.0031162866,0.00972438,4.0950843e-7,0.00038062927,0.0012137662,0.00006753172],"about_ca_topic_score_codex":0.0051299897,"about_ca_topic_score_gemma":0.17183475,"teacher_disagreement_score":0.16670476,"about_ca_system_score_codex":0.0002324934,"about_ca_system_score_gemma":0.00043758404,"threshold_uncertainty_score":0.8432771},"labels":[],"label_agreement":null},{"id":"W4413790900","doi":"10.23889/ijpds.v10i4.3198","title":"Standardizing health data stewardship principles and practices in Canada","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Institute for Health Information; University of British Columbia","funders":"","keywords":"Stewardship (theology); Business; Data science; Environmental resource management; Computer science; Political science; Environmental science","score_opus":0.7483561638667391,"score_gpt":0.6878237297325048,"score_spread":0.06053243413423426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413790900","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7199667,0.0013252526,0.012444324,0.25581554,0.0054716743,0.0010184278,0.0025176054,0.000021050782,0.0014193977],"genre_scores_gemma":[0.9842551,0.00082099263,0.012887284,0.0013415118,0.00015358387,0.0000018506933,0.0003441438,0.0000040641335,0.00019151307],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99700016,0.000052677675,0.000555551,0.0004299442,0.001753458,0.00020823],"domain_scores_gemma":[0.99497736,0.0026502346,0.0005216234,0.0008005785,0.0008622326,0.00018795347],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.013832057,0.000056202145,0.00013777782,0.00027570943,0.00023354178,0.00026564882,0.0019122896,0.000030509942,0.000010201357],"category_scores_gemma":[0.06551188,0.00004810468,0.000008804379,0.00029275467,0.00012380656,0.0015433806,0.0013366331,0.0006187814,2.754525e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023804457,0.00004649215,0.9296007,0.000096010604,0.000038019905,0.000023541985,0.000048081605,0.00012592257,0.00005777527,0.025547842,0.0021874888,0.041990064],"study_design_scores_gemma":[0.001035134,0.000056329125,0.8851185,0.0008535413,0.0000108885015,0.00006385829,0.00046522822,0.061782546,0.000021919373,0.0084331585,0.042081863,0.00007703553],"about_ca_topic_score_codex":0.3822265,"about_ca_topic_score_gemma":0.87285405,"teacher_disagreement_score":0.4906276,"about_ca_system_score_codex":0.0010715007,"about_ca_system_score_gemma":0.01596147,"threshold_uncertainty_score":0.9896171},"labels":[],"label_agreement":null},{"id":"W4413791511","doi":"10.23889/ijpds.v10i4.3307","title":"A Way Home: Understanding the impact of human trafficking on Inuit women in Manitoba","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Sex work and related issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Human trafficking; Environmental health; Psychology; Criminology; Medicine","score_opus":0.10686663126341973,"score_gpt":0.44346626280979323,"score_spread":0.3365996315463735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413791511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958881,0.000025731397,0.0005877529,0.0008489387,0.001041826,0.00014628035,0.000016291482,0.000009724236,0.001435351],"genre_scores_gemma":[0.99954534,0.000035828212,0.00004910948,0.00003484806,0.00014810865,0.0000025408674,0.0000130116705,0.0000028423674,0.00016836605],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9986017,0.00006541643,0.00028497112,0.00016613824,0.00063664955,0.00024512399],"domain_scores_gemma":[0.99925697,0.00018581205,0.00018303901,0.0001634442,0.00015782873,0.000052901116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031130216,0.00005933372,0.00008894556,0.0004995123,0.000813417,0.00034359377,0.0016169482,0.00003827192,0.0000461284],"category_scores_gemma":[0.00059209083,0.00004002489,0.000043856682,0.0006911778,0.00027160943,0.00080731814,0.00010661501,0.00016186446,0.0000010652278],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035820113,0.0004081428,0.31998694,0.000009933408,0.00029099948,0.000015657452,0.17347132,0.03592849,0.00215513,0.41399318,0.0026808497,0.050701156],"study_design_scores_gemma":[0.0016402133,0.00023549065,0.60515517,0.0007304879,0.000019785743,0.000009274761,0.115945086,0.017730104,0.000078351724,0.2565701,0.0015823505,0.0003035736],"about_ca_topic_score_codex":0.002419137,"about_ca_topic_score_gemma":0.0022242195,"teacher_disagreement_score":0.28516823,"about_ca_system_score_codex":0.0019479614,"about_ca_system_score_gemma":0.00032063905,"threshold_uncertainty_score":0.6256228},"labels":[],"label_agreement":null},{"id":"W4413791582","doi":"10.23889/ijpds.v10i4.3304","title":"Indigenous community engagement in administrative data research: Lessons from the Qanuinngitsiarutiksait study","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Indigenous; Community engagement; Data science; Political science; Public relations; Computer science; Biology; Ecology","score_opus":0.7878515511889046,"score_gpt":0.658492292451105,"score_spread":0.12935925873779963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413791582","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9702948,0.00015822034,0.0010880004,0.015407577,0.005212631,0.0026239625,0.0036685697,0.000018769257,0.0015274662],"genre_scores_gemma":[0.9968429,0.000099684104,0.000489187,0.0006987305,0.00029811732,0.0000835422,0.0012391974,0.0000061875503,0.00024243328],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9952167,0.002046274,0.00073561555,0.00041951818,0.0008872906,0.00069457677],"domain_scores_gemma":[0.99304163,0.0038529052,0.00029772066,0.0015149796,0.0012289494,0.00006381785],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.028798278,0.000104385974,0.0001735455,0.0003584145,0.01613612,0.00018562106,0.007930516,0.000057921978,0.000082987666],"category_scores_gemma":[0.007058774,0.00007555528,0.000018463055,0.0006512069,0.00025380903,0.0010469472,0.006675948,0.0018376168,0.000022674541],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022693214,0.0008706085,0.86913854,0.000008718631,0.00017572037,0.00001489109,0.096646026,0.000058192636,0.000022585144,0.0065098833,0.016656477,0.009671401],"study_design_scores_gemma":[0.00087510713,0.00012264457,0.79747975,0.00008684946,0.00001658564,0.000001855908,0.1539143,0.0014842193,0.0000013201478,0.005321143,0.04061609,0.0000801585],"about_ca_topic_score_codex":0.051881656,"about_ca_topic_score_gemma":0.3474226,"teacher_disagreement_score":0.29554096,"about_ca_system_score_codex":0.00092684134,"about_ca_system_score_gemma":0.0019377766,"threshold_uncertainty_score":0.99809664},"labels":[],"label_agreement":null},{"id":"W4413792002","doi":"10.23889/ijpds.v10i4.3226","title":"Experiences of the Red River Métis with COVID-19 Policy Decisions: A partnership-based, whole-population linked administrative data study","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Disaster Response and Management","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Health Sciences Centre; Manitoba Health","funders":"","keywords":"General partnership; Coronavirus disease 2019 (COVID-19); Population; Business; Environmental health; Medicine; Finance","score_opus":0.3601440549093614,"score_gpt":0.5887294019987864,"score_spread":0.22858534708942502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413792002","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9072343,0.00002874385,0.068653695,0.017081836,0.0026604736,0.0028160568,0.0008051529,0.00003913981,0.0006806018],"genre_scores_gemma":[0.9944427,0.000005576748,0.0023419934,0.001424274,0.0001707628,0.00010109113,0.0005162073,0.000006724413,0.0009906519],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967403,0.00040994244,0.00076952775,0.0005213602,0.0012811373,0.00027772514],"domain_scores_gemma":[0.9963631,0.00087180105,0.00075712317,0.0013088821,0.0005533945,0.0001457214],"candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.0034568235,0.00013060129,0.00017224971,0.00055610144,0.0014869346,0.00015465727,0.0043081422,0.000042471765,0.000050896993],"category_scores_gemma":[0.008925778,0.0000836117,0.000034875797,0.000956575,0.0002821647,0.0018220464,0.0014900251,0.00021130117,0.0000033245994],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0051898556,0.0013970998,0.8023183,0.00009706669,0.0003917248,0.000026946605,0.06495662,0.003879659,0.00016729443,0.055715896,0.046254136,0.019605404],"study_design_scores_gemma":[0.0062412927,0.0004833351,0.6774948,0.001044648,0.0001683472,0.000012977253,0.14552242,0.032332223,0.000017649121,0.010378655,0.12592536,0.00037827072],"about_ca_topic_score_codex":0.0010195993,"about_ca_topic_score_gemma":0.0016267899,"teacher_disagreement_score":0.12482347,"about_ca_system_score_codex":0.00036348338,"about_ca_system_score_gemma":0.002555784,"threshold_uncertainty_score":0.999813},"labels":[],"label_agreement":null},{"id":"W4413929356","doi":"10.23889/ijpds.v10i3.2973","title":"Considerations for selecting and implementing comorbidity indices when using secondary data sources: a guide for health researchers","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"South Health Campus; Alberta Health Services; University of Calgary","funders":"Alberta Innovates; Killam Trusts","keywords":"Data science; Comorbidity; Computer science; Data mining; Medicine; Psychiatry","score_opus":0.46575322914147327,"score_gpt":0.5694136286888988,"score_spread":0.10366039954742551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413929356","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2757864,0.0010301565,0.65105057,0.053808022,0.002738202,0.0050168736,0.009723395,0.000101793084,0.00074459147],"genre_scores_gemma":[0.74285376,0.000081409635,0.24914816,0.0020987531,0.00065725704,0.000036921097,0.0047751754,0.000018367247,0.00033019314],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981936,0.000029353085,0.0005208182,0.0004503977,0.000484275,0.00032155434],"domain_scores_gemma":[0.9980204,0.0005240236,0.0003489215,0.00040082098,0.00058795686,0.00011785862],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004634677,0.000089030036,0.00014960016,0.00043146012,0.0013056097,0.00084404636,0.00077012484,0.0000198098,0.00003370421],"category_scores_gemma":[0.0043949205,0.000086671746,0.000030318683,0.00016122458,0.00013334911,0.0021436296,0.00077403156,0.000118281474,1.238921e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014106698,0.0005952344,0.19492169,0.0027452249,0.0021956866,0.000016485159,0.0026805606,0.002001846,0.006146204,0.115620844,0.4341814,0.23748416],"study_design_scores_gemma":[0.0062354733,0.00020930263,0.036722783,0.0008320652,0.00025618798,0.00014428108,0.0036996254,0.7030027,0.00013756978,0.045639183,0.20283587,0.00028494964],"about_ca_topic_score_codex":0.0004923929,"about_ca_topic_score_gemma":0.0008120413,"teacher_disagreement_score":0.70100087,"about_ca_system_score_codex":0.00033780487,"about_ca_system_score_gemma":0.0020799432,"threshold_uncertainty_score":0.9999946},"labels":[],"label_agreement":null},{"id":"W4415702020","doi":"10.23889/ijpds.v10i1.2968","title":"Regional and sociodemographic variation of incident first-episode psychosis in Ontario, Canada","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Schizophrenia research and treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Women's College Hospital; University of Toronto; Centre for Addiction and Mental Health; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Psychosis; Variation (astronomy); Regional variation; Plan (archaeology); Outpatient clinic; Incidence (geometry)","score_opus":0.04917561052355941,"score_gpt":0.3703791825124166,"score_spread":0.3212035719888572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415702020","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898724,0.000087625805,0.0011303286,0.008047779,0.00056056096,0.00020029343,0.000052899406,0.0000027173996,0.00004537591],"genre_scores_gemma":[0.9946153,0.00006856869,0.004845088,0.00017454762,0.000035217345,0.000008498303,0.00016251765,0.0000021440485,0.00008810933],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986495,0.000011707978,0.00029466624,0.00020331332,0.0007206571,0.00012017842],"domain_scores_gemma":[0.9991841,0.000088824025,0.00012765788,0.00016855777,0.0003510183,0.000079844445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057458406,0.000056779434,0.0001020314,0.00044095796,0.0001274019,0.00005264087,0.00035511577,0.000021574704,0.000028685381],"category_scores_gemma":[0.0003452854,0.00004879745,0.000023124468,0.00025676482,0.00007104936,0.00046024242,0.00009803997,0.000119696575,1.399274e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056892046,0.0000635358,0.9909245,0.000006836259,0.00004550882,0.000005725424,0.000041052386,0.00006673671,0.00004537821,0.004016932,0.0010947868,0.0031201073],"study_design_scores_gemma":[0.001430711,0.000035465524,0.9875451,0.00011783242,0.000015640275,0.00003900784,0.00001960973,0.0052467086,0.000019399122,0.0041824523,0.0013135349,0.000034540735],"about_ca_topic_score_codex":0.88609284,"about_ca_topic_score_gemma":0.9901113,"teacher_disagreement_score":0.10401848,"about_ca_system_score_codex":0.0007285641,"about_ca_system_score_gemma":0.001050913,"threshold_uncertainty_score":0.19899023},"labels":[],"label_agreement":null},{"id":"W4415873365","doi":"10.23889/ijpds.v10i1.2976","title":"Co-producing data-intensive research with an underserved group: a case study and evaluation identifying pathways to impact","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Mental Health and Patient Involvement","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Economic and Social Research Council; Queen's University; UK Research and Innovation","keywords":"Bespoke; General partnership; Context (archaeology); Thematic analysis; Representativeness heuristic; Participatory action research; Health care; Participatory evaluation; Work (physics); Resource (disambiguation)","score_opus":0.858727344345991,"score_gpt":0.6877034746249917,"score_spread":0.17102386972099926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415873365","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9895304,0.00002700402,0.0044573112,0.0007037688,0.0017167155,0.002895006,0.00060854806,0.000015352283,0.000045896013],"genre_scores_gemma":[0.99367,0.000006541309,0.0023669698,0.00084303407,0.0002499421,0.000080561025,0.0027466395,0.000009060921,0.000027249456],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99567175,0.00064361,0.000652186,0.00074974756,0.0018383574,0.0004443588],"domain_scores_gemma":[0.9940744,0.00041871276,0.00028805636,0.0009239957,0.0039764764,0.00031834585],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.020340312,0.00011448867,0.0001442847,0.0008173002,0.0031225912,0.00029527396,0.0013913531,0.000034741377,0.000044407665],"category_scores_gemma":[0.0016218618,0.00008776378,0.000010624596,0.000695209,0.000072385024,0.0031094248,0.00073568284,0.00040435442,0.000008113363],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015764446,0.0005321253,0.9245365,0.00019086833,0.00012994009,0.00014578695,0.020910088,0.0005682537,0.000724644,0.0010040478,0.0035985687,0.04608273],"study_design_scores_gemma":[0.005875434,0.002389475,0.46934026,0.0019652182,0.000107419386,0.00040618298,0.24873504,0.2664165,0.000026559526,0.00357407,0.0008000127,0.0003638376],"about_ca_topic_score_codex":0.010241322,"about_ca_topic_score_gemma":0.015890663,"teacher_disagreement_score":0.45519623,"about_ca_system_score_codex":0.0009537421,"about_ca_system_score_gemma":0.0011614771,"threshold_uncertainty_score":0.9981752},"labels":[],"label_agreement":null},{"id":"W4416297172","doi":"10.23889/ijpds.v10i1.2984","title":"Poverty and intellectual development in childhood","year":2025,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Cognitive Abilities and Testing","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"Canadian Institutes of Health Research","keywords":"Poverty; Mental health; Child poverty; Intellectual development; Early childhood; Child development; Intellectual ability","score_opus":0.06993541138108703,"score_gpt":0.41140540565435546,"score_spread":0.3414699942732684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416297172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9809603,0.00011752787,0.011304657,0.0011429925,0.0027398882,0.00016084444,0.00005628724,0.00001271014,0.003504758],"genre_scores_gemma":[0.99607325,0.000007547816,0.002797443,0.0005485959,0.00007712464,0.0000054586462,0.000054043307,0.0000025791117,0.00043396812],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991159,0.000016821654,0.00026505618,0.0002463157,0.00021629217,0.00013960313],"domain_scores_gemma":[0.99927455,0.00029516628,0.00006949744,0.00012132322,0.0002045062,0.00003496155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008709825,0.00005347874,0.00005962612,0.0003482903,0.00018341621,0.00015490594,0.00058934395,0.000018138178,0.0001519519],"category_scores_gemma":[0.002262262,0.00004839557,0.000010603793,0.00021922823,0.00006319949,0.00056730927,0.00029019298,0.00010075588,0.000004594995],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000081514845,0.00015221481,0.32767528,0.0000044689987,0.000042857206,0.0000064062015,0.0023559828,0.00002025224,0.00008269794,0.030439455,0.0037143903,0.6354245],"study_design_scores_gemma":[0.00060759735,0.000017426408,0.9576901,0.00006952917,0.000002961617,0.00005608962,0.0005577513,0.0018572025,0.000028922837,0.0039692638,0.035068266,0.0000748997],"about_ca_topic_score_codex":0.00010228355,"about_ca_topic_score_gemma":0.00010745522,"teacher_disagreement_score":0.6353496,"about_ca_system_score_codex":0.00010036295,"about_ca_system_score_gemma":0.00013843764,"threshold_uncertainty_score":0.2708302},"labels":[],"label_agreement":null}]}