{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":6,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":6,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"036f871055d5","filters":{"venue":"Healthcare Engineering"}},"results":[{"id":"W4415569876","doi":"10.5267/j.he.2025.1.006","title":"Benchmarking rehabilitation efficiency across Canadian provinces: An implementation of TOPSIS analysis of throughput and budget allocation","year":2025,"lang":"","type":"article","venue":"Healthcare Engineering","topic":"Healthcare Systems and Practices","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"TOPSIS; Benchmarking; Resource allocation; Limiting; Order (exchange); Quality (philosophy); Throughput; Service (business); Grid","authors":[{"name":"Sepideh Sadat Sadjadi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0352830744381072,"gpt":0.4529960621112573,"spread":0.4177129876731501,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008143575,0.0009538584,0.001235181,0.00804267,0.002636793,0.00357552,0.00121815,0.0003720339,0.002023057],"category_scores_gemma":[0.02564651,0.0003939596,0.001897607,0.0182875,0.0007532986,0.000715929,0.001323552,0.000689311,0.0001427892],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04551731,"about_ca_system_score_gemma":0.08117212,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9702638,"about_ca_topic_score_gemma":0.9587917,"domain_scores_codex":[0.9918333,0.002113604,0.000622221,0.0005271704,0.003699906,0.00120362],"domain_scores_gemma":[0.9889424,0.002331516,0.0007907155,0.0004242431,0.007178852,0.0003322902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005151044,0.0002556338,0.5562041,0.001013844,0.001465926,0.0003976362,0.006013815,0.1491124,0.001722998,0.01513526,0.01049361,0.2576697],"study_design_scores_gemma":[0.00008175964,0.000277659,0.6484743,0.0003070152,0.0005414566,0.00009844327,0.01979356,0.313013,0.002161452,0.003449086,0.01158621,0.00021606],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9303005,0.000598487,0.03987198,0.0009646908,0.00006394842,0.0008866788,0.005541014,0.0002732383,0.02149945],"genre_scores_gemma":[0.9590213,0.0002971766,0.03740343,0.0000330013,0.000004612084,0.0002238112,0.001811047,0.00002397854,0.00118166],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9544827,"threshold_uncertainty_score":0.3302528,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415569926","doi":"10.5267/j.he.2025.1.003","title":"Provincial analysis of relative efficiency in Canadian hospitals using DEA","year":2025,"lang":"","type":"article","venue":"Healthcare Engineering","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Data envelopment analysis; Efficiency; Investment (military); Measure (data warehouse); Resource allocation","authors":[{"name":"Reza Ghaeli","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02891930926755639,"gpt":0.3566528685063978,"spread":0.3277335592388415,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002930065,0.0004992292,0.0006183729,0.002622364,0.0007156081,0.00170534,0.000559263,0.0002027819,0.001218763],"category_scores_gemma":[0.01027987,0.0002054621,0.001060319,0.005765834,0.0004279779,0.0003315646,0.0006784241,0.000598194,0.00009063388],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02011517,"about_ca_system_score_gemma":0.01576637,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9107919,"about_ca_topic_score_gemma":0.8648506,"domain_scores_codex":[0.9978672,0.0005503962,0.0001087565,0.0001853921,0.0008352935,0.0004529405],"domain_scores_gemma":[0.9959824,0.001579241,0.0003460951,0.0002799745,0.001712182,0.0001001272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001666113,0.00008720049,0.1608419,0.000157847,0.000334718,0.0001069116,0.0002475592,0.7725154,0.0007469117,0.02452841,0.001673822,0.03859285],"study_design_scores_gemma":[0.00001770904,0.00004189921,0.1530472,0.00003544077,0.00008229608,0.00003252157,0.0005812031,0.8372755,0.001150583,0.003575793,0.004120469,0.00003936983],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9243523,0.000359905,0.05198926,0.0003681139,0.00001810935,0.0001765851,0.004601407,0.0001358265,0.01799857],"genre_scores_gemma":[0.9849516,0.0001837841,0.01162749,0.00001718753,0.000003116693,0.00004511578,0.001596965,0.00001405848,0.001560582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9798849,"threshold_uncertainty_score":0.1794669,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415569904","doi":"10.5267/j.he.2025.1.001","title":"Barriers to timely medication access in Canada: Implications for healthcare policy","year":2025,"lang":"","type":"article","venue":"Healthcare Engineering","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Referral; Equity (law); Healthcare policy; Health care; Healthcare system; Key (lock); Benchmark (surveying); Health policy","authors":[{"name":"Hasti Bagherzadi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04332540958665981,"gpt":0.3876854366427825,"spread":0.3443600270561227,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005128877,0.0003507237,0.0007335026,0.002515448,0.009592758,0.007280288,0.002683842,0.002815459,0.006424854],"category_scores_gemma":[0.02300434,0.000415513,0.001079259,0.004783169,0.003801125,0.002486692,0.002841007,0.003328054,0.0001865293],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.2162019,"about_ca_system_score_gemma":0.472389,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9970579,"about_ca_topic_score_gemma":0.9974902,"domain_scores_codex":[0.9906808,0.001009623,0.0003815628,0.0004224659,0.002524693,0.004980895],"domain_scores_gemma":[0.975924,0.004761206,0.002711229,0.0002690006,0.006932371,0.009402129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004378184,0.0008036954,0.4420663,0.00276923,0.0004703099,0.00214161,0.01618097,0.00963929,0.001372589,0.1622039,0.1359347,0.2259795],"study_design_scores_gemma":[0.0002226732,0.0002952142,0.7833729,0.00444953,0.0004213477,0.0004921368,0.04388252,0.01199776,0.0008153649,0.02718221,0.1264305,0.0004377895],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2185176,0.0192667,0.001079959,0.7146019,0.0004282249,0.0003088281,0.002192139,0.0001023258,0.04350236],"genre_scores_gemma":[0.9519772,0.0100435,0.00238995,0.03011393,0.0001679892,0.00009537972,0.0004667701,0.00002325645,0.004721959],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2162019,"threshold_uncertainty_score":0.9090947,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415569922","doi":"10.5267/j.he.2025.1.005","title":"Benchmarking rehabilitation efficiency across Canadian provinces: A DEA-based analysis of throughput and budget allocation","year":2025,"lang":"","type":"article","venue":"Healthcare Engineering","topic":"Healthcare Systems and Practices","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Benchmarking; Resource allocation; Rehabilitation; Investment (military); Throughput; Resource (disambiguation); Service (business); Software deployment","authors":[{"name":"Rouzbeh Ghousi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03087190982744937,"gpt":0.4066298408143197,"spread":0.3757579309868703,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004206812,0.0005498648,0.0008180552,0.00713151,0.002145184,0.002864364,0.001269451,0.0003012786,0.001454898],"category_scores_gemma":[0.01671122,0.0003079723,0.001070343,0.0180685,0.000607905,0.0005295585,0.001365477,0.0005959061,0.0001515122],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0964991,"about_ca_system_score_gemma":0.1064867,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9973751,"about_ca_topic_score_gemma":0.9966659,"domain_scores_codex":[0.9943983,0.0008846617,0.000341789,0.0004051655,0.002434018,0.001536078],"domain_scores_gemma":[0.9903386,0.001544844,0.0008504994,0.0004466145,0.00629399,0.0005254582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004039369,0.0001101006,0.859469,0.0003234523,0.0008383587,0.0001443852,0.002095605,0.04331795,0.0004756456,0.01070431,0.0118418,0.07027543],"study_design_scores_gemma":[0.00002173757,0.0000477428,0.9573944,0.00008864114,0.0001287516,0.00003780107,0.004234101,0.02557494,0.0003802229,0.0005073996,0.01153146,0.00005278285],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9469277,0.00106231,0.003996911,0.000955927,0.00003282014,0.0002664374,0.02430547,0.0001175175,0.0223349],"genre_scores_gemma":[0.9873875,0.0004052699,0.003080164,0.00007206601,0.000004491048,0.00009388044,0.006795151,0.00002538504,0.002136139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9035009,"threshold_uncertainty_score":0.7001532,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415569910","doi":"10.5267/j.he.2025.1.004","title":"Evaluating primary care efficiency across Canadian provinces: A DEA-based approac","year":2025,"lang":"","type":"article","venue":"Healthcare Engineering","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Primary care; Data envelopment analysis; Scale (ratio); Nova scotia; Payment; Resource allocation; Health care; Resource (disambiguation); Primary health care","authors":[{"name":"Ahmad Makui","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.056149558545935,"gpt":0.3188352905224172,"spread":0.2626857319764822,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01066713,0.001355144,0.001861846,0.00363152,0.001451104,0.004069614,0.001658718,0.0005914487,0.00145984],"category_scores_gemma":[0.03874626,0.0006365196,0.001974212,0.007834514,0.0008595982,0.0008903328,0.001483626,0.0008353795,0.0001386067],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05041339,"about_ca_system_score_gemma":0.06217976,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9691246,"about_ca_topic_score_gemma":0.9373689,"domain_scores_codex":[0.9902385,0.003181033,0.000416558,0.001045928,0.003966673,0.001151205],"domain_scores_gemma":[0.9853166,0.005676806,0.001012485,0.001207675,0.006516368,0.0002700214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002540429,0.0001154917,0.1140284,0.0003785019,0.001022258,0.0000973398,0.0003095654,0.8107267,0.000532133,0.01798507,0.002717108,0.05183343],"study_design_scores_gemma":[0.00008218884,0.0001225732,0.1002627,0.0001236354,0.0003541523,0.00005934021,0.000889528,0.8842115,0.0009466037,0.005609321,0.007263716,0.00007473537],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8080491,0.003381872,0.138857,0.002211252,0.00007389477,0.001036607,0.01261154,0.0004688038,0.03330984],"genre_scores_gemma":[0.963601,0.0007366911,0.03111861,0.000123744,0.00001132605,0.0001393181,0.002976193,0.00004073952,0.001252349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9495866,"threshold_uncertainty_score":0.3657764,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415569936","doi":"10.5267/j.he.2025.1.002","title":"Measuring the relative efficiency of MRI/CT unit in Canada: Implications for healthcare policy","year":2025,"lang":"","type":"article","venue":"Healthcare Engineering","topic":"Radiology practices and education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Data envelopment analysis; Efficiency; Unit (ring theory); Measure (data warehouse); Health care; Empirical evidence; Empirical research","authors":[{"name":"Hasti Bagherzadi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05785381004352444,"gpt":0.3562216713970781,"spread":0.2983678613535536,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008028599,0.0003990059,0.0007080744,0.003749588,0.001599623,0.003118389,0.0007994125,0.0004489939,0.001156261],"category_scores_gemma":[0.03796683,0.0002480061,0.0006124889,0.009424499,0.001486915,0.001345978,0.001174319,0.000848364,0.00006987003],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06542505,"about_ca_system_score_gemma":0.07319797,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.954808,"about_ca_topic_score_gemma":0.935665,"domain_scores_codex":[0.9892439,0.003801455,0.0006150672,0.0005844935,0.003810108,0.001945002],"domain_scores_gemma":[0.9834729,0.007973305,0.002042318,0.0004846652,0.005306677,0.0007200674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003133003,0.0001858388,0.6209217,0.0004378942,0.000604998,0.0002574765,0.001013813,0.1939249,0.0009574984,0.08962952,0.003206467,0.0885465],"study_design_scores_gemma":[0.00006938227,0.0001748088,0.7723172,0.0004156438,0.0003368297,0.0001290642,0.006511859,0.1867067,0.002404182,0.02022685,0.01061221,0.00009523174],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9212587,0.002615802,0.02421275,0.009382948,0.00002701723,0.0003684335,0.003239234,0.00008085973,0.03881416],"genre_scores_gemma":[0.9902173,0.0007266431,0.007742662,0.0001662518,0.000007813024,0.00002976098,0.0003793304,0.000008361823,0.000721996],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.934575,"threshold_uncertainty_score":0.4746942,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}