{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":340,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":340,"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"},"query_hash":"2c0236da869a","filters":{"venue":"Methods in Ecology and Evolution"}},"results":[{"id":"W1526319989","doi":"10.1111/j.2041-210x.2011.00172.x","title":"Selecting pseudo‐absences for species distribution models: how, where and how many?","year":2012,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":2840,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Agence Nationale de la Recherche; European Commission","keywords":"Regression; Environmental niche modelling; Statistics; Species distribution; Regression analysis; Distribution (mathematics); Prediction interval; Predictive modelling; Computer science; Machine learning; Mathematics; Ecology; Artificial intelligence; Econometrics; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.06044548630036738,"gpt":0.3214334075925124,"spread":0.260987921292145,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001190108,0.0001059271,0.0001462812,0.00002531523,0.0002601358,0.00003029312,0.00005428321,0.0001461913,0.0003110457],"category_scores_gemma":[0.0002127399,0.00009951965,0.00002521197,0.0001461552,0.0002343665,0.0004625606,0.00008632799,0.0001008162,0.000004868122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004145695,"about_ca_system_score_gemma":0.000004009239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003476831,"about_ca_topic_score_gemma":0.000586429,"domain_scores_codex":[0.999048,0.0002111201,0.00009397641,0.0002143624,0.00006391743,0.0003686151],"domain_scores_gemma":[0.9995698,0.0002131858,0.0000685324,0.00006944675,0.00001065708,0.00006831568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003155296,0.00007026006,0.9560522,0.00003409931,0.000008143239,3.175888e-7,0.0004375204,0.00002754011,0.00473316,0.028038,0.004907638,0.005659518],"study_design_scores_gemma":[0.0003173231,0.00007166341,0.971743,0.000005621118,0.00001633452,0.00001885787,0.004224334,0.008885024,0.0005228861,0.005217763,0.00882945,0.0001477694],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8702972,0.0006871297,0.1244492,0.00223552,0.0003349528,0.0002538417,0.00004522493,0.00003167875,0.001665262],"genre_scores_gemma":[0.982429,0.0003382013,0.01653645,0.00004073168,0.00005635733,0.00006198494,0.00003443606,0.000004997041,0.0004978491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1121318,"threshold_uncertainty_score":0.4058293,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3035663944","doi":"10.1111/2041-210x.13434","title":"Robustness of linear mixed‐effects models to violations of distributional assumptions","year":2020,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":1352,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"Deutsche Forschungsgemeinschaft; National Science Foundation","keywords":"Heteroscedasticity; Random effects model; Statistics; Mathematics; Residual; Econometrics; Variance (accounting); Robustness (evolution); Mixed model; Best linear unbiased prediction; Computer science; Algorithm; Selection (genetic algorithm); Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.0342764187613661,"gpt":0.3272200656833215,"spread":0.2929436469219554,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004255295,0.00005761597,0.0001641099,0.00003974476,0.00009666206,6.884596e-7,0.00005616159,0.00009435064,0.00004425539],"category_scores_gemma":[0.0003508785,0.00005896689,0.0000242028,0.0002456641,0.0001938294,0.00008416536,0.0001041121,0.00008641409,0.0000043199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005960026,"about_ca_system_score_gemma":0.000008123418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002171862,"about_ca_topic_score_gemma":0.0003189069,"domain_scores_codex":[0.9992068,0.0002782519,0.0002118886,0.000150929,0.00004574423,0.0001063887],"domain_scores_gemma":[0.9993935,0.0004235438,0.00007274533,0.00005254085,0.00001813436,0.00003948743],"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":[0.00001996944,0.00006107354,0.4588775,0.00001819949,0.00001052367,2.125068e-7,0.0003268962,0.5293499,0.002719366,0.008182159,0.00005284013,0.0003813498],"study_design_scores_gemma":[0.0001287053,0.00007070372,0.6400674,0.0000034277,0.00001147922,6.471914e-7,0.00004547048,0.353715,0.0002140363,0.005698835,0.000008509845,0.00003582765],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4592673,0.00002543497,0.5400403,0.0003463432,0.00007379278,0.00009403701,0.000008774854,0.000004702359,0.0001393812],"genre_scores_gemma":[0.7669643,0.00001143765,0.2329309,0.00004139988,0.000008483081,0.0000242266,0.000006639008,0.000001851262,0.00001078485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3076971,"threshold_uncertainty_score":0.24046,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4205237613","doi":"10.1111/2041-210x.13800","title":"Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package","year":2022,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":1144,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"R package; Generalization; Regression analysis; Regression; Variation (astronomy); Multilevel model; Computer science; Canonical correlation; Interpretation (philosophy); Segmented regression; Generalized additive model; Statistics; Mathematics; Polynomial regression","retraction":null,"screen_n_in":null,"score":{"opus":0.07056167024889846,"gpt":0.3905592479178542,"spread":0.3199975776689557,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001707113,0.00006666097,0.0001253363,0.0000675891,0.0007489136,0.000007934577,0.00003819001,0.00006712271,0.00004978666],"category_scores_gemma":[0.0003207418,0.00005426832,0.00001079617,0.0001812514,0.0002773273,0.00009667784,0.0002759235,0.0002539731,2.879734e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001835341,"about_ca_system_score_gemma":0.000009882257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004871022,"about_ca_topic_score_gemma":0.007122351,"domain_scores_codex":[0.9979663,0.001425041,0.0001788593,0.0002215726,0.00005217489,0.0001560044],"domain_scores_gemma":[0.9991943,0.0006555092,0.00006703276,0.00005888132,0.000003124298,0.00002121553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002479236,0.00002649969,0.9719096,0.000003047914,0.000005446712,0.00000288142,0.001151074,0.01787656,0.007275319,0.0008103,0.000005227395,0.0009092743],"study_design_scores_gemma":[0.0002380246,0.0000299407,0.7209761,0.000002647298,0.000009850421,0.00001549609,0.0002966473,0.2710841,0.00001741546,0.007263715,0.00002094791,0.00004515536],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978331,0.0003382609,0.02052308,0.0005208541,0.00009766807,0.0001111844,0.000001442477,0.000006029864,0.00007046464],"genre_scores_gemma":[0.9568955,0.00008249452,0.04282518,0.0001210494,0.000009735204,0.00004237884,0.000002713622,0.000003026823,0.00001785728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2532076,"threshold_uncertainty_score":0.5760113,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1482160415","doi":"10.1111/j.2041-210x.2012.00234.x","title":"Diversitree: comparative phylogenetic analyses of diversification in R","year":2012,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":990,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Genetic algorithm; Extinction (optical mineralogy); R package; Phylogenetic tree; Trait; Macroevolution; Biology; Evolutionary biology; Statistics; Computer science; Mathematics; Genetics; Paleontology","retraction":null,"screen_n_in":null,"score":{"opus":0.1539268253782782,"gpt":0.4100778764929515,"spread":0.2561510511146733,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007164971,0.00006029721,0.0001869146,0.0001911318,0.00007000472,0.000001150099,0.00004905165,0.00008479937,0.000103384],"category_scores_gemma":[0.00007743902,0.00005490316,0.00001787994,0.0002374103,0.0002190048,0.0001050643,0.00001159286,0.00008257874,0.0000104423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001147201,"about_ca_system_score_gemma":0.000009588183,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001033166,"about_ca_topic_score_gemma":0.02698135,"domain_scores_codex":[0.9988772,0.000642128,0.0001603883,0.0001092331,0.00003740023,0.0001736115],"domain_scores_gemma":[0.9994227,0.0004057974,0.00007114743,0.00005266945,0.00001819573,0.00002945209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003320727,0.00002756252,0.9959406,0.000006274778,0.00001282523,2.889807e-7,0.00107606,0.0004652448,0.0002222247,0.000169933,0.00001957736,0.002026217],"study_design_scores_gemma":[0.0002397894,0.00004927857,0.994881,0.000003386741,0.0000177341,0.000001732171,0.001326387,0.002537549,0.00009290253,0.0007578612,0.0000382967,0.00005409171],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887736,0.00508464,0.002160467,0.00005563443,0.0001988165,0.00007948757,0.000005883478,0.000004901078,0.003636595],"genre_scores_gemma":[0.9817293,0.0001498449,0.01805978,0.00001944845,0.0000133565,0.000001109273,0.000007707359,3.794748e-7,0.00001908603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02594818,"threshold_uncertainty_score":0.9907737,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1969068219","doi":"10.1111/2041-210x.12069","title":"pavo: an R package for the analysis, visualization and organization of spectral data","year":2013,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":689,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"","keywords":"Workflow; Visualization; Computer science; Variety (cybernetics); Data visualization; R package; Data science; Range (aeronautics); Data mining; Computer graphics (images); Artificial intelligence; Database","retraction":null,"screen_n_in":null,"score":{"opus":0.04873047395761101,"gpt":0.3709734421214391,"spread":0.3222429681638281,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007096305,0.00004436139,0.00008989028,0.00003402423,0.00009717351,0.00001148702,0.00009186652,0.00006000548,0.002530162],"category_scores_gemma":[0.0002494952,0.00003406232,0.000008039932,0.0003798279,0.0001447826,0.0002162459,0.00009384139,0.00002864797,0.000004993421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007113667,"about_ca_system_score_gemma":0.000002990144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002715866,"about_ca_topic_score_gemma":0.001831644,"domain_scores_codex":[0.9994102,0.00017235,0.0001237221,0.0001634133,0.00003660011,0.00009367803],"domain_scores_gemma":[0.999587,0.0001521459,0.00005952335,0.000166622,0.00001369166,0.00002101563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003822727,0.00003803374,0.9883081,0.000004253166,0.00001473892,3.046429e-8,0.0002012256,0.00002926192,0.005339501,0.003481534,0.0002512458,0.002328194],"study_design_scores_gemma":[0.0001344534,0.00002991374,0.969804,4.618191e-7,0.00006405178,9.312532e-7,0.000953357,0.02730554,0.0004723479,0.001054398,0.0001420963,0.00003842502],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7663339,0.00004094344,0.2331537,0.0001544289,0.00004392484,0.0001755068,0.0000208163,0.000006586603,0.00007019581],"genre_scores_gemma":[0.992827,0.0001097796,0.006740067,0.0000495795,0.000008942256,0.00001267086,0.0002250388,0.00000293903,0.00002396745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2264931,"threshold_uncertainty_score":0.9983817,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2954932437","doi":"10.1111/2041-210x.13256","title":"Applications for deep learning in ecology","year":2019,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":681,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"Polar Knowledge Canada","keywords":"Deep learning; Artificial intelligence; Computer science; Data science; Flexibility (engineering); Process (computing); Machine learning; Ecology; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.02241791783830923,"gpt":0.3402525461178592,"spread":0.31783462827955,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007967787,0.0000534834,0.0001109313,0.0000476894,0.00006660688,0.000003565807,0.00005658556,0.0001304103,0.003525114],"category_scores_gemma":[0.0001085265,0.00005676559,0.00001707749,0.0001575844,0.00008632235,0.00005778057,0.00005926081,0.0001137396,0.0002175966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004622822,"about_ca_system_score_gemma":0.000004504501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004288373,"about_ca_topic_score_gemma":0.002925917,"domain_scores_codex":[0.9992585,0.0001883177,0.0001315342,0.0001979436,0.00002485909,0.0001988634],"domain_scores_gemma":[0.9996039,0.0002618778,0.00004076028,0.0000665821,0.000004144397,0.00002276365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001470848,0.00004144347,0.9835032,0.000006415017,0.000001144187,1.570874e-7,0.00007511519,0.000306015,0.001480585,0.004336818,0.00004220202,0.01019217],"study_design_scores_gemma":[0.000400608,0.00006686975,0.969486,8.522047e-7,0.000002700596,0.00000281187,0.00058261,0.004094101,0.00004980298,0.004520142,0.02073253,0.00006096006],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9509028,0.00006499587,0.03941736,0.0003408663,0.0001570094,0.0005150984,0.00000265079,0.00001997022,0.008579307],"genre_scores_gemma":[0.983192,0.0000464319,0.01578403,0.000130176,0.000009714229,0.0003398127,0.00001856767,0.000004081169,0.0004752096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03228923,"threshold_uncertainty_score":0.9973858,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2105841516","doi":"10.1111/j.2041-210x.2010.00078.x","title":"Testing the significance of canonical axes in redundancy analysis","year":2010,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":636,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Rural Development Administration","keywords":"Permutation (music); Type I and type II errors; Canonical analysis; Redundancy (engineering); Mathematics; Statistics; Resampling; Computer science; Algorithm; Biplot; Raw data; Canonical correlation; Data mining","retraction":null,"screen_n_in":null,"score":{"opus":0.1203185544981921,"gpt":0.4753799399020894,"spread":0.3550613854038973,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00353793,0.00007438377,0.000314988,0.0001277845,0.00005692717,0.000002994614,0.0000865613,0.0001311658,0.00001729409],"category_scores_gemma":[0.01221679,0.00005476747,0.00003199546,0.0005553613,0.0002645807,0.00003914189,0.00004101678,0.0003692413,1.760734e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003148368,"about_ca_system_score_gemma":0.00004824531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001488523,"about_ca_topic_score_gemma":0.004231668,"domain_scores_codex":[0.9983361,0.0008707137,0.0003657836,0.0001933024,0.00005034089,0.0001837907],"domain_scores_gemma":[0.9904492,0.009181772,0.0001231871,0.0001745137,0.00004531609,0.00002599303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004547289,0.0001487215,0.4067476,0.0000582199,0.00004879357,0.000004292002,0.0004064155,0.0006711913,0.04349111,0.4936051,0.00000690668,0.05476619],"study_design_scores_gemma":[0.0001031136,0.00002538559,0.4308648,0.000004516556,0.00004966584,0.000001885157,0.00005020485,0.01879767,0.0002859561,0.5497651,0.00001092629,0.00004075707],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3569155,0.00003031888,0.6423771,0.00008496812,0.0000839691,0.0001136154,0.000002942249,0.000006109114,0.0003854202],"genre_scores_gemma":[0.4722673,0.000002559375,0.5276711,0.000008515185,0.000009730728,0.00002267526,2.267203e-7,0.000002658507,0.0000152799],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1153517,"threshold_uncertainty_score":0.9961037,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2281654679","doi":"10.1111/2041-210x.12528","title":"Integrated step selection analysis: bridging the gap between resource selection and animal movement","year":2015,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":633,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Killam Trusts; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Alberta Conservation Association","keywords":"Computer science; Selection (genetic algorithm); Resource (disambiguation); Inference; Model selection; Set (abstract data type); Variety (cybernetics); Data mining; Machine learning; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.03296824317286588,"gpt":0.3101507573624712,"spread":0.2771825141896053,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002950363,0.00009423814,0.0001594545,0.0001211733,0.000248069,0.00001453398,0.00005759449,0.0001632955,0.0000447134],"category_scores_gemma":[0.0002393429,0.00007803417,0.00002093591,0.0008036269,0.0001527213,0.0001616647,0.00007327806,0.0002358288,0.000006693427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003426656,"about_ca_system_score_gemma":0.00001958546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008391202,"about_ca_topic_score_gemma":0.005644046,"domain_scores_codex":[0.9980816,0.001168447,0.0002089427,0.0002702707,0.00007385408,0.000196838],"domain_scores_gemma":[0.9995586,0.0002172014,0.00009413066,0.00006633541,0.00001504847,0.000048663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005319091,0.00001945461,0.9900789,0.000001350326,0.00004686152,2.759338e-7,0.0002130936,0.002134359,0.0004859051,0.0001487622,0.0004524063,0.006365471],"study_design_scores_gemma":[0.000241406,0.0001512007,0.8943228,0.000001744014,0.0001276522,0.000004721888,0.0002748767,0.101968,0.0000864692,0.002184536,0.0005623779,0.00007427463],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8992624,0.00004389345,0.09922245,0.0009300825,0.0000520449,0.0001549258,8.289011e-7,0.00002664944,0.0003067813],"genre_scores_gemma":[0.9782031,0.000006239626,0.02125117,0.0003126973,0.00004566581,0.00003377028,0.000007955749,0.000004186467,0.0001352487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09983362,"threshold_uncertainty_score":0.3182141,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2746877260","doi":"10.1111/2041-210x.12869","title":"Diet tracing in ecology: Method comparison and selection","year":2017,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":550,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of New Brunswick","funders":"","keywords":"Trophic level; Selection (genetic algorithm); Ecology; Tracing; Biology; Resource (disambiguation); Computer science; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.02525143103323987,"gpt":0.3840804431286101,"spread":0.3588290120953702,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004014028,0.000124281,0.0003696112,0.0001522386,0.0004218486,0.00002169312,0.0001555821,0.000314466,0.000178277],"category_scores_gemma":[0.0008805416,0.0001293841,0.00002497113,0.0001365295,0.0003865581,0.0002822116,0.000256952,0.0003505457,0.00001837807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003632168,"about_ca_system_score_gemma":0.00001112648,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008625415,"about_ca_topic_score_gemma":0.04969981,"domain_scores_codex":[0.9974862,0.001352451,0.0003294362,0.0004343998,0.00005243545,0.0003451073],"domain_scores_gemma":[0.9990705,0.0005162701,0.0001970037,0.0001663439,0.000006375694,0.00004352452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005409194,0.0000726264,0.9763402,0.000005116074,0.000008707565,0.000003665411,0.0003156328,0.001906324,0.002129194,0.0003011113,0.00004336696,0.01881992],"study_design_scores_gemma":[0.0004435554,0.0001824,0.907985,0.000003472649,0.00002329342,0.00001872018,0.000133259,0.07961521,0.0002819685,0.01100197,0.0001956706,0.0001154805],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9473722,0.00005589882,0.04911706,0.0004333005,0.0002208291,0.0001883344,4.3361e-7,0.00001430408,0.002597671],"genre_scores_gemma":[0.768483,0.00003852034,0.2312188,0.00007585985,0.00001770626,0.00003863208,7.502254e-7,0.000005465287,0.0001212659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1821018,"threshold_uncertainty_score":0.9676407,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2952113774","doi":"10.1111/2041-210x.13120","title":"Machine learning to classify animal species in camera trap images: Applications in ecology","year":2018,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":481,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Saskatchewan","funders":"National Energy Technology Laboratory; Animal and Plant Health Inspection Service; University of Saskatchewan; National Wildlife Research Center; Colorado Parks and Wildlife; University of Georgia Research Foundation; University of Wyoming; U.S. Department of Agriculture; U.S. Department of Energy","keywords":"Artificial intelligence; Computer science; Camera trap; Wildlife; Laptop; Convolutional neural network; Sample (material); Citizen science; Machine learning; Cartography; Geography; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.0209818672774687,"gpt":0.3171276760884255,"spread":0.2961458088109568,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001524957,0.000109853,0.0002037058,0.0002151706,0.0001615631,0.000005908959,0.0001148073,0.0002460696,0.0004867258],"category_scores_gemma":[0.0003529783,0.0001168396,0.00001680233,0.0005346839,0.0004122688,0.0001481574,0.0001179379,0.0003531541,0.00009754496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003826841,"about_ca_system_score_gemma":0.00002131965,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005083311,"about_ca_topic_score_gemma":0.03765652,"domain_scores_codex":[0.9981486,0.0008313843,0.0002926782,0.000362604,0.00004312887,0.0003216341],"domain_scores_gemma":[0.9993519,0.0004236195,0.00006713697,0.0001051633,0.000008017515,0.0000441755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006503553,0.00009101834,0.9926175,0.000002754527,0.00000214851,0.000002513806,0.0005476518,0.0004028531,0.002759968,0.0006895324,0.0001014535,0.002717501],"study_design_scores_gemma":[0.0003818741,0.0002758933,0.9878868,0.000003260946,0.000004395285,0.000006431886,0.000344767,0.004488466,0.000114391,0.003878055,0.002503425,0.0001122747],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863719,0.0000378191,0.00872125,0.00173918,0.0001240751,0.0003359416,0.000001679757,0.00001965066,0.002648497],"genre_scores_gemma":[0.9613001,0.00002904281,0.03755362,0.0004796899,0.0000394307,0.0001832305,0.000006241766,0.000006300225,0.0004023187],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03714819,"threshold_uncertainty_score":0.9799038,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2751943544","doi":"10.1111/2041-210x.12861","title":"The <scp>bien r</scp> package: A tool to access the Botanical Information and Ecology Network (BIEN) database","year":2017,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":411,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"European Research Council; Academy of Natural Sciences of Drexel University; Bhabha Atomic Research Centre; University of California; University of California, Santa Barbara; Ministry of Business, Innovation and Employment; Agence Nationale de Sécurité du Médicament et des Produits de Santé; Canada Foundation for Innovation; American Museum of Natural History; Centre International de Mathématiques et Informatique de Toulouse; Fondation pour la Recherche sur la Biodiversite; Commonwealth Health Research Board; Villum Fonden; National Science Foundation","keywords":"R package; Database; Ecology; Geography; Computer science; World Wide Web; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.03819843962422658,"gpt":0.3548965569274348,"spread":0.3166981173032082,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002717069,0.00009695578,0.000125125,0.0000167755,0.001406833,0.0001728596,0.0003957023,0.0001310102,0.0002919815],"category_scores_gemma":[0.002251135,0.00006328352,0.00001946079,0.0001132596,0.0005465663,0.0006993377,0.0009232001,0.0001952407,0.0001061698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002332566,"about_ca_system_score_gemma":0.00001151992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001353724,"about_ca_topic_score_gemma":0.005151308,"domain_scores_codex":[0.9987446,0.0004006371,0.0002244959,0.0001870199,0.00008367188,0.0003595522],"domain_scores_gemma":[0.9986173,0.0007988568,0.0001410159,0.0003656245,0.00001203311,0.00006518288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002817828,0.00002680129,0.9541569,0.000005138533,0.000007878177,0.000001525691,0.0002901303,0.00007332814,0.0001650791,0.007173216,0.01647769,0.02159412],"study_design_scores_gemma":[0.0002493674,0.00005336666,0.9276722,0.000002403877,0.000009826772,0.00001299686,0.0005235738,0.0008879407,0.00002551395,0.002748333,0.06777818,0.00003630922],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842964,0.0000755478,0.007822212,0.002604565,0.0006295416,0.0003911663,0.00002324212,0.00001643194,0.004140902],"genre_scores_gemma":[0.9932553,0.0004546289,0.004091636,0.001732242,0.00007210567,0.0001581231,0.00002122937,0.000005132422,0.0002096241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05130048,"threshold_uncertainty_score":0.9998932,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1931677568","doi":"10.1111/2041-210x.12425","title":"Should the Mantel test be used in spatial analysis?","year":2015,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":395,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mantel test; Statistics; Homoscedasticity; Mathematics; Spatial analysis; Correlation; Null hypothesis; Regression analysis; Canonical correlation; Heteroscedasticity; Population; Demography","retraction":null,"screen_n_in":null,"score":{"opus":0.163148900173195,"gpt":0.3579848147825169,"spread":0.1948359146093219,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003563586,0.00009435785,0.0003940477,0.0005451487,0.00006008021,0.00001955947,0.0001479071,0.0001687368,0.0001356056],"category_scores_gemma":[0.001124765,0.00008314429,0.00006706402,0.0009026185,0.00009641784,0.0001147108,0.00006707387,0.0002033277,0.00003126411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001226493,"about_ca_system_score_gemma":0.00001767047,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007880381,"about_ca_topic_score_gemma":0.05121201,"domain_scores_codex":[0.9988025,0.0002232815,0.0004414778,0.0002979032,0.00002484898,0.0002099981],"domain_scores_gemma":[0.9990672,0.0004968794,0.0001478477,0.0002268543,0.00001650715,0.00004473513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001500765,0.00005993399,0.9915581,0.000002702417,0.00004541114,0.000002526364,0.0003233177,0.0007809032,0.000009292344,0.006141349,0.00007543543,0.0009860584],"study_design_scores_gemma":[0.0003710034,0.00004572903,0.89205,0.000001118239,0.00004967554,0.000001504479,0.0001772169,0.07425349,0.000009795348,0.03172272,0.001222638,0.00009506696],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7574337,0.001021068,0.2350586,0.003122159,0.00044841,0.000188564,0.00008223305,0.00001737274,0.002627941],"genre_scores_gemma":[0.9912759,0.00007429728,0.008122179,0.0002504953,0.00005164152,0.00002621759,0.00003340608,0.000004921379,0.0001609597],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2338422,"threshold_uncertainty_score":0.9987262,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2553804235","doi":"10.1111/2041-210x.12700","title":"Bioinformatic processing of RAD‐seq data dramatically impacts downstream population genetic inference","year":2016,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":375,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Trent University","funders":"Svenska Forskningsrådet Formas; Royal Swedish Academy of Sciences; Wenner-Gren Foundation","keywords":"Population; Biology; Transversion; Inference; Statistics; Genetics; Data mining; Computational biology; Computer science; Mathematics; Artificial intelligence; Mutation","retraction":null,"screen_n_in":null,"score":{"opus":0.02594557484420514,"gpt":0.3484616913044795,"spread":0.3225161164602744,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004655953,0.00008949369,0.00014468,0.00008362153,0.00005485549,0.000007297276,0.0001511405,0.0002008457,0.00001914883],"category_scores_gemma":[0.0005954597,0.00006864339,0.00001672387,0.00009348617,0.0001048403,0.00002171009,0.0001673068,0.00004664829,0.000001508056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001736345,"about_ca_system_score_gemma":0.00005181159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002645299,"about_ca_topic_score_gemma":0.0001131103,"domain_scores_codex":[0.9991152,0.0001937728,0.0002811129,0.0001994386,0.00005932399,0.0001511288],"domain_scores_gemma":[0.9994399,0.00005522228,0.0001470401,0.0002687282,0.00004740924,0.00004173161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005059153,0.00002185714,0.8688011,0.00007519389,0.00001274233,3.261784e-7,0.00006630937,0.0001187876,0.04265518,0.0001772128,0.00003572441,0.08798496],"study_design_scores_gemma":[0.0004552481,0.0001047409,0.9909729,0.00003490341,0.00002028601,0.00001208169,0.00003840933,0.001910778,0.001686087,0.004562211,0.0001091495,0.00009315265],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8207764,0.0001816586,0.1786062,0.000103994,0.00008524477,0.0001085576,0.00001615569,0.000005179758,0.0001166557],"genre_scores_gemma":[0.8580558,0.00007681133,0.141724,0.00002899266,0.0000229656,0.000002228157,0.00005990717,0.000003359085,0.00002601974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1221718,"threshold_uncertainty_score":0.2799196,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2122737105","doi":"10.1111/j.2041-210x.2010.00083.x","title":"Methods for collaboratively identifying research priorities and emerging issues in science and policy","year":2011,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":371,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Natural Environment Research Council; Sight Research UK; Canada Research Chairs; Arcadia Fund","keywords":"Rigour; Openness to experience; Political science; Identification (biology); Science policy; Public relations; Management science; Sociology; Public administration; Economics; Ecology; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.1303081201323294,"gpt":0.5113446688958423,"spread":0.3810365487635129,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01168992,0.00007576129,0.0001380737,0.000528469,0.0003545179,0.00003243635,0.0001098887,0.00007240084,0.0000445739],"category_scores_gemma":[0.001953112,0.00007501568,0.000006177967,0.00106798,0.00150232,0.0004471719,0.0003585193,0.0001269599,0.000003199469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002273075,"about_ca_system_score_gemma":0.00004393471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002753434,"about_ca_topic_score_gemma":0.001840472,"domain_scores_codex":[0.9982731,0.0007966048,0.0001633714,0.0003081209,0.00008896712,0.0003698236],"domain_scores_gemma":[0.9993792,0.0004246737,0.0000376248,0.00008396267,0.00002652148,0.00004808783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006905754,0.00003733513,0.8098906,0.00006355764,0.000004715186,0.000001573971,0.01635365,0.000007477469,0.01105307,0.05784206,0.0002541316,0.1044228],"study_design_scores_gemma":[0.0002532486,0.0001007523,0.900902,0.00001022037,0.000003283844,0.000002098679,0.001026431,0.003638793,0.0006254766,0.09078324,0.002574082,0.00008040429],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9817142,0.000848102,0.009213227,0.0007671957,0.0001318356,0.000525923,0.00000117635,0.00001348142,0.006784798],"genre_scores_gemma":[0.4195104,0.0003500658,0.5792881,0.00004751551,0.00002371149,0.00006738763,2.173885e-7,0.00000479351,0.0007077772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5700749,"threshold_uncertainty_score":0.5535361,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2097691827","doi":"10.1111/j.2041-210x.2010.00084.x","title":"Measuring individual differences in reaction norms in field and experimental studies: a power analysis of random regression models","year":2010,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":361,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal; Université Laval; Université de Sherbrooke","funders":"Biotechnology and Biological Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Natural Environment Research Council; Sight Research UK","keywords":"Censoring (clinical trials); Statistics; Regression analysis; Regression; Multilevel model; Random effects model; Variance (accounting); Statistical power; Econometrics; Rule of thumb; Computer science; Variation (astronomy); Mathematics; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.09841758150070137,"gpt":0.3634928284266175,"spread":0.2650752469259161,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001163773,0.00006681174,0.000257197,0.0001112835,0.00005347171,0.000004139244,0.00003680976,0.000154546,0.00001118107],"category_scores_gemma":[0.0001687131,0.00002813242,0.00002677592,0.0003629614,0.00007950189,0.0001302545,0.00004232708,0.000178626,6.938718e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002296818,"about_ca_system_score_gemma":0.000002637646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000512309,"about_ca_topic_score_gemma":0.007005225,"domain_scores_codex":[0.9991587,0.0002514097,0.0002079341,0.0002228464,0.00005589549,0.000103202],"domain_scores_gemma":[0.9995842,0.0002851931,0.00006961655,0.00002720619,0.00001758612,0.00001620659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001319486,0.00007224778,0.6797502,0.000002051544,0.00001256773,5.518106e-7,0.0007587872,0.000009074159,0.3128076,0.00004175734,4.21358e-7,0.006412822],"study_design_scores_gemma":[0.0002799043,0.0001652873,0.988659,0.00001181003,0.00003037878,0.000002223414,0.002735168,0.0006339219,0.006458996,0.0009669522,9.668207e-7,0.00005544994],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990616,0.0005180892,0.00003650667,0.00009667109,0.0001502983,0.0001024464,0.000001056666,0.000005039694,0.00002824292],"genre_scores_gemma":[0.9987593,0.00011098,0.001079814,0.000006616303,0.00001419251,0.00001918557,0.00000251054,2.971351e-7,0.000007159655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3089088,"threshold_uncertainty_score":0.390908,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2046705466","doi":"10.1111/2041-210x.12198","title":"Measuring habitat fragmentation: An evaluation of landscape pattern metrics","year":2014,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":341,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba; University of Alberta","funders":"Directorate for Biological Sciences; York University; Alberta-Pacific Forest Industries; Natural Sciences and Engineering Research Council of Canada; Arizona State University","keywords":"Fragmentation (computing); Habitat; Habitat fragmentation; Abundance (ecology); Spatial ecology; Ecology; Metric (unit); Breeding bird survey; Landscape ecology; Landscape connectivity; Range (aeronautics); Geography; Biology; Population","retraction":null,"screen_n_in":null,"score":{"opus":0.05148392063707805,"gpt":0.3467057975317215,"spread":0.2952218768946435,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00534425,0.00006350128,0.0001316566,0.0001044631,0.0001079201,0.000002951647,0.00005503121,0.00009909185,0.0001384626],"category_scores_gemma":[0.000625034,0.00006327578,0.00001464297,0.000204063,0.0001283493,0.0001563483,0.00005198144,0.00008531376,0.000009666716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001153567,"about_ca_system_score_gemma":0.000006443863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004396707,"about_ca_topic_score_gemma":0.003768459,"domain_scores_codex":[0.9980937,0.001272973,0.0002018535,0.0001848547,0.0001261144,0.000120528],"domain_scores_gemma":[0.999409,0.0003501535,0.00009955238,0.00008739633,0.00003059097,0.00002335896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006032931,0.00004538328,0.9414591,0.000005852685,0.000006064665,8.010265e-8,0.0003760483,0.01020035,0.0003709528,0.000235001,0.000006778819,0.0472884],"study_design_scores_gemma":[0.0003566684,0.00008616022,0.7415631,0.000002070947,0.00002506648,0.000001424103,0.0001412299,0.2448086,0.00007673159,0.01288337,0.000008536089,0.00004710675],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8709306,0.00008950203,0.1265754,0.00007411688,0.0001874741,0.0001166198,5.188794e-7,0.000008047611,0.00201779],"genre_scores_gemma":[0.9567307,0.00001865554,0.04313105,0.00005392225,0.00001276656,0.00003290115,0.000004363644,0.00000323261,0.00001237138],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2346082,"threshold_uncertainty_score":0.2580312,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2103516605","doi":"10.1111/2041-210x.12034","title":"<scp>SURFACE</scp>: detecting convergent evolution from comparative data by fitting Ornstein‐Uhlenbeck models with stepwise Akaike Information Criterion","year":2013,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":328,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Harvard University","keywords":"Akaike information criterion; Convergent evolution; Convergence (economics); Phylogenetic tree; Mathematics; Surface (topology); Bayesian information criterion; Tree (set theory); Statistics; Clade; R package; Selection (genetic algorithm); Evolutionary biology; Applied mathematics; Biology; Statistical physics; Computer science; Artificial intelligence; Combinatorics; Gene; Genetics; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.05786323045324158,"gpt":0.3078917892129863,"spread":0.2500285587597447,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001251669,0.0002391417,0.0004031922,0.0001364797,0.0004767834,0.00005613799,0.0002282392,0.0002627983,0.0001169364],"category_scores_gemma":[0.0003469042,0.0002064438,0.00002459276,0.0002760224,0.0002911947,0.002307937,0.00007361432,0.0003570727,0.00009044854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005569034,"about_ca_system_score_gemma":0.00006211433,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.00844992,"about_ca_topic_score_gemma":0.0335731,"domain_scores_codex":[0.9973847,0.001046049,0.0005183335,0.0004411256,0.0001544252,0.0004553264],"domain_scores_gemma":[0.9978434,0.001333376,0.000298565,0.000287777,0.0001286144,0.0001082301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004070025,0.00002270564,0.9842227,0.00002312467,0.00005664273,8.843252e-7,0.001879966,0.006986267,0.0001602499,0.00007965894,0.001747232,0.004779934],"study_design_scores_gemma":[0.000486158,0.0001248364,0.6088345,0.00002195383,0.00002758135,0.000008434093,0.004106218,0.3837671,0.00002689361,0.002056105,0.0004499345,0.00009025096],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8335568,0.002990862,0.1601809,0.000129822,0.0004757032,0.0004507221,0.0001315967,0.00006547164,0.002018098],"genre_scores_gemma":[0.9086406,0.0001410015,0.09056453,0.0001369808,0.00003754949,0.00001161896,0.0003985473,0.000003227428,0.0000659556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3767809,"threshold_uncertainty_score":0.9981529,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2325650867","doi":"10.1111/2041-210x.12569","title":"<scp>codyn</scp>: An<scp>r</scp>package of community dynamics metrics","year":2016,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":311,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"University of California; National Science Foundation","keywords":"R package; Stability (learning theory); Computer science; Null model; Covariance; Diversity (politics); Rank (graph theory); Term (time); Ecology; Data science; Statistics; Machine learning; Mathematics; Biology; Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.02390098146871047,"gpt":0.3202976342511605,"spread":0.29639665278245,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00375899,0.000164078,0.0003359303,0.0002021123,0.0003825249,0.000005203679,0.0002534647,0.0003562543,0.00002891271],"category_scores_gemma":[0.005476156,0.0001357701,0.00004649306,0.0004955121,0.0009451436,0.0002995899,0.0003457072,0.0003578605,0.00003568521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003982221,"about_ca_system_score_gemma":0.00001604435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001822021,"about_ca_topic_score_gemma":0.008322423,"domain_scores_codex":[0.996716,0.002182941,0.0003793135,0.00024463,0.0001002568,0.0003768835],"domain_scores_gemma":[0.9931913,0.006176111,0.0002252429,0.0003007207,0.00003191317,0.00007469144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003887567,0.0002350825,0.984868,0.00001647344,0.00002456817,0.000001589655,0.001242344,0.0002481566,0.002141169,0.005187491,0.0002462285,0.005785001],"study_design_scores_gemma":[0.00047995,0.000278866,0.9365228,0.000006193487,0.00002866367,0.00000862774,0.001481001,0.007307997,0.0002809399,0.05325724,0.0003100673,0.0000376269],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8581994,0.0001241276,0.1343528,0.00009651942,0.0003058486,0.0001555148,0.00001630955,0.00002939181,0.00672009],"genre_scores_gemma":[0.9405431,0.0002384644,0.05795049,0.0001231162,0.00001283498,0.0000303566,0.000009202973,0.00001101447,0.001081431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08234365,"threshold_uncertainty_score":0.6555866,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2063051191","doi":"10.1111/2041-210x.12166","title":"Using commonality analysis in multiple regressions: a tool to decompose regression effects in the face of multicollinearity","year":2014,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":311,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Lakehead University","funders":"","keywords":"Multicollinearity; Variance inflation factor; Regression analysis; Regression; Statistics; Variance (accounting); Econometrics; Regression diagnostic; Multilevel model; Computer science; Mathematics; Polynomial regression","retraction":null,"screen_n_in":null,"score":{"opus":0.1347669155526959,"gpt":0.472230184712616,"spread":0.3374632691599201,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003569081,0.0001219442,0.0004468541,0.0003128523,0.0001277767,0.000004771176,0.0001155384,0.0001627096,0.000004309763],"category_scores_gemma":[0.001938405,0.00008649774,0.00006238451,0.0007079229,0.000105512,0.00006249049,0.0001487935,0.0002497169,7.226203e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000109803,"about_ca_system_score_gemma":0.00001076681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001410062,"about_ca_topic_score_gemma":0.004053683,"domain_scores_codex":[0.9955649,0.003508295,0.0003823925,0.0002578228,0.00007971757,0.0002068677],"domain_scores_gemma":[0.9975685,0.002065904,0.0001048689,0.0002062402,0.00003171515,0.00002272531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004269258,0.0002201529,0.9828035,0.00003521987,0.00001596114,0.00001038344,0.001152268,0.0007275703,0.009482458,0.0001421342,0.000003130695,0.004980249],"study_design_scores_gemma":[0.0006289381,0.0002074376,0.9388114,0.00006139128,0.00006843171,0.000005070095,0.0004318702,0.05882394,0.0001138769,0.0007440445,0.00001209659,0.00009154184],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9476388,0.0001662329,0.05158542,0.0001287973,0.00007135843,0.0003717948,0.000004149942,0.000007731668,0.00002569451],"genre_scores_gemma":[0.8908226,0.000008571673,0.1090543,0.00004661613,0.000009152161,0.00005038653,0.000002710314,0.000003924754,0.000001813505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05809637,"threshold_uncertainty_score":0.3527276,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2131387099","doi":"10.1111/j.2041-210x.2012.00246.x","title":"Using species combinations in indicator value analyses","year":2012,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":307,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Indicator value; Indicator species; Abundance (ecology); Species groups; Range (aeronautics); Ecology; Habitat; Rare species; Community structure; Common species; Biology; Genus","retraction":null,"screen_n_in":null,"score":{"opus":0.09110208361635687,"gpt":0.4268025635860035,"spread":0.3357004799696467,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001210704,0.0000606368,0.000125851,0.0001351705,0.0001457702,0.000002438317,0.00004414214,0.0001069901,0.0001409756],"category_scores_gemma":[0.000239198,0.00006031087,0.00001445761,0.0002462193,0.0002748028,0.0001826473,0.00008728116,0.0001238806,0.00001933914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002630266,"about_ca_system_score_gemma":0.000005507041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001057487,"about_ca_topic_score_gemma":0.001347652,"domain_scores_codex":[0.9989566,0.0005185037,0.0001613494,0.0001203213,0.00003517308,0.0002080521],"domain_scores_gemma":[0.9995518,0.0003088277,0.0000556755,0.00005442285,0.000002667898,0.00002658736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003187071,0.0001114697,0.9883506,0.000002213998,0.000005310233,4.204501e-7,0.0005764106,0.002344358,0.001236677,0.007170269,0.000009897039,0.0001891404],"study_design_scores_gemma":[0.0002101166,0.00001579987,0.9709738,0.000001822464,0.00001129792,0.000003907599,0.0002637885,0.01528179,0.00006444545,0.01305764,0.00005471501,0.00006085736],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9684888,0.0002347183,0.02781888,0.0001314118,0.0002171767,0.00008400857,6.9962e-7,0.000007848627,0.003016528],"genre_scores_gemma":[0.8992785,0.00003662139,0.1005117,0.00006512299,0.00001005911,0.00001413931,0.000001289601,0.000002371285,0.00008018303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07269285,"threshold_uncertainty_score":0.2459406,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2794549961","doi":"10.1111/2041-210x.13009","title":"<scp>tRophicPosition</scp>, an<scp>r</scp>package for the Bayesian estimation of trophic position from consumer stable isotope ratios","year":2018,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":306,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of New Brunswick","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico; Comisión Nacional de Investigación Científica y Tecnológica; Ministerio de Economía, Fomento y Turismo, Chile; Academy of Finland","keywords":"Trophic level; Markov chain Monte Carlo; Baseline (sea); Bayesian probability; Environmental science; Food chain; Population; Ecology; Position (finance); Computer science; Statistics; Econometrics; Mathematics; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.01363580757093485,"gpt":0.3015053024057481,"spread":0.2878694948348133,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001969259,0.0001829349,0.0003410472,0.0001359836,0.0004778271,0.00002491794,0.0002376303,0.0003173221,0.0002014815],"category_scores_gemma":[0.001670935,0.0001589891,0.00006691951,0.000366495,0.0008262454,0.0004644183,0.0001150992,0.0001989203,0.00005200769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002775513,"about_ca_system_score_gemma":0.0000342313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004410161,"about_ca_topic_score_gemma":0.001859109,"domain_scores_codex":[0.9973412,0.001177859,0.0004878734,0.0004650733,0.000135128,0.0003929079],"domain_scores_gemma":[0.9963562,0.002840464,0.000299049,0.0003825638,0.00005842895,0.00006321642],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001421962,0.0008680976,0.7029539,0.00005330869,0.0003020656,0.000007801472,0.004875288,0.02670764,0.2338094,0.005769846,0.006062718,0.01844766],"study_design_scores_gemma":[0.0007147041,0.0005645384,0.7121263,0.000008497669,0.0001869609,0.000011506,0.0004949316,0.2354687,0.01204016,0.03765908,0.0006687457,0.00005596934],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.544102,0.0001035005,0.4544973,0.0001201831,0.0002310813,0.0004569202,0.00001936771,0.00001726908,0.0004523345],"genre_scores_gemma":[0.7957399,0.00004903203,0.2034181,0.0002475002,0.00008299184,0.0001812004,0.0000580695,0.00001490712,0.0002082239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2516379,"threshold_uncertainty_score":0.6483386,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1975931252","doi":"10.1111/2041-210x.12037","title":"High sensitivity of 454 pyrosequencing for detection of rare species in aquatic communities","year":2013,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":297,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University; University of Guelph; Fisheries and Oceans Canada; University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; Health Canada; Ministerio de Economía y Competitividad; Chinese Academy of Sciences","keywords":"Pyrosequencing; Biology; Environmental DNA; Biodiversity; Species complex; Metagenomics; Rare species; Ecology; Genetics; Gene; Habitat; Phylogenetic tree","retraction":null,"screen_n_in":null,"score":{"opus":0.02822068319598402,"gpt":0.267936538635153,"spread":0.239715855439169,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009380779,0.00005987179,0.0001743247,0.00006123662,0.00007209131,0.000001420223,0.00003977672,0.00007467359,0.00005023654],"category_scores_gemma":[0.0001581893,0.00006180732,0.00001916147,0.00008533084,0.0005326938,0.0001274877,0.0001251316,0.00007419556,0.000003510607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002543405,"about_ca_system_score_gemma":0.000001284323,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009713447,"about_ca_topic_score_gemma":0.01053695,"domain_scores_codex":[0.9991009,0.0004811026,0.0001701583,0.00008955931,0.00004428285,0.0001139714],"domain_scores_gemma":[0.9991635,0.0006615645,0.00008572848,0.00007570229,0.000003412467,0.0000100618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001224653,0.00003349656,0.8532529,0.00001906436,0.000003839807,1.791505e-7,0.0009947848,0.0005105865,0.1431089,0.00002678102,0.000005020385,0.00203219],"study_design_scores_gemma":[0.0002333127,0.00009814019,0.9614245,0.000009998629,0.000007134852,0.000001326128,0.004463799,0.002767876,0.02738868,0.003550116,0.000003335458,0.00005178794],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848603,0.00002860678,0.01467654,0.00004091037,0.00007369457,0.0002429199,0.000004186094,0.00000388185,0.00006896067],"genre_scores_gemma":[0.882857,0.00003113642,0.1170567,0.00001166033,0.000002784491,0.00001820398,0.000001683803,0.000001869816,0.00001900339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1157203,"threshold_uncertainty_score":0.9968809,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1980344423","doi":"10.1111/2041-210x.12197","title":"Landscape connectivity for wildlife: development and validation of multispecies linkage maps","year":2014,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":294,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Ministry of Natural Resources and Forestry; Trent University","funders":"Ministry of Natural Resources","keywords":"Wildlife; Grid cell; Habitat; Grid; Current (fluid); Site selection; Wildlife conservation; Node (physics); Perimeter; Geography; Computer science; Cartography; Environmental science; Ecology; Geology; Biology; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.02019846344956613,"gpt":0.3048219237308411,"spread":0.2846234602812749,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001127191,0.00005633471,0.0001165116,0.00004783793,0.00009836329,0.000005377813,0.00002818554,0.00007984908,0.00003738618],"category_scores_gemma":[0.000350729,0.00005463136,0.00001122367,0.0000698208,0.00008266422,0.0001373873,0.00003877632,0.00005281791,0.000002473523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000572735,"about_ca_system_score_gemma":0.000006626869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006275059,"about_ca_topic_score_gemma":0.0003715747,"domain_scores_codex":[0.9993334,0.0002163232,0.0001674648,0.0001550003,0.00003447383,0.00009334873],"domain_scores_gemma":[0.9993771,0.0004561781,0.00007934868,0.00005813299,0.00001044436,0.00001879363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002827946,0.0000409516,0.9655038,0.00001434659,0.000004448432,4.578859e-8,0.0002883083,0.000222219,0.003045265,0.0008735955,0.0001976921,0.02978112],"study_design_scores_gemma":[0.0003607573,0.0000679411,0.9761152,0.000007064144,0.000006727056,0.000002865007,0.0001024006,0.01166342,0.00315693,0.003396565,0.005058517,0.0000616434],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8489714,0.00001499622,0.1501573,0.0002104649,0.0001124895,0.0001338745,0.000001430632,0.000007040889,0.0003909752],"genre_scores_gemma":[0.8076392,0.000008302416,0.1921453,0.00006767458,0.00001306444,0.00003889047,0.000006340952,0.0000025569,0.00007865152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04198796,"threshold_uncertainty_score":0.2227802,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2163690261","doi":"10.1111/2041-210x.12103","title":"Inferring food web structure from predator–prey body size relationships","year":2013,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":257,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Rimouski","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Food web; Predation; Niche; Ecology; Pelagic zone; Novelty; Food chain; Apex predator; Ecosystem; Biology; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01623945223204344,"gpt":0.2825960407665199,"spread":0.2663565885344765,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008117169,0.0001239995,0.0002141799,0.00006917244,0.0002028325,0.00001535865,0.0001541281,0.0003369124,0.00430452],"category_scores_gemma":[0.001443313,0.0001216702,0.0000303278,0.000233286,0.0002158365,0.0003417463,0.0002299517,0.0004016029,0.0001671774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002908026,"about_ca_system_score_gemma":0.00001511117,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002305467,"about_ca_topic_score_gemma":0.01976321,"domain_scores_codex":[0.9977663,0.001225031,0.0002915252,0.0003602227,0.0000723926,0.0002845467],"domain_scores_gemma":[0.9984163,0.001180227,0.0001026497,0.0002331097,0.000009718294,0.00005801941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005296279,0.00002492527,0.9876135,0.000001634465,0.00001837944,6.523757e-7,0.0002037393,0.0009384,0.009437192,0.0002858747,0.000240893,0.001229526],"study_design_scores_gemma":[0.0002547788,0.00005963762,0.9041868,0.000002177378,0.0000251108,0.000004120711,0.00011259,0.01296953,0.0002686444,0.08168776,0.00031496,0.0001138292],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910707,0.00006902714,0.00645038,0.000202201,0.000269541,0.0002435346,0.00000941385,0.00003057078,0.001654615],"genre_scores_gemma":[0.8542169,0.00001466849,0.1454195,0.0001139859,0.00003324039,0.00005095675,0.000006569872,0.000007696255,0.0001364293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1389691,"threshold_uncertainty_score":0.9981236,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2132578265","doi":"10.1111/j.2041-210x.2011.00103.x","title":"A simple polytomy resolver for dated phylogenies","year":2011,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":244,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"Luonnontieteiden ja Tekniikan Tutkimuksen Toimikunta; Natural Environment Research Council; Sight Research UK","keywords":"Supertree; Phylogenetic tree; Phylogenomics; Phylogenetics; Coalescent theory; Evolutionary biology; Biology; Supermatrix; Tree (set theory); Statistics; Mathematics; Clade; Genetics; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.07178877186270276,"gpt":0.3382656840313056,"spread":0.2664769121686028,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009060506,0.00009245849,0.0001834886,0.0001215102,0.0002077593,0.00000364586,0.00007394158,0.0001530164,0.0003201901],"category_scores_gemma":[0.0002587218,0.00008081184,0.00003061518,0.0001314494,0.0002411059,0.00009131684,0.00001142982,0.0000992518,0.00001532092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006558745,"about_ca_system_score_gemma":0.00002146102,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009102561,"about_ca_topic_score_gemma":0.07109956,"domain_scores_codex":[0.9989378,0.0003529672,0.0001834858,0.0002202667,0.00002914791,0.00027627],"domain_scores_gemma":[0.9993507,0.000436633,0.00005466434,0.00008740286,0.00002922411,0.00004136913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001326183,0.00001456216,0.9920794,0.000008597889,0.00001923552,0.000001535121,0.0004000414,0.00001049376,0.00004415687,0.001148408,0.0003441623,0.005796778],"study_design_scores_gemma":[0.0004002351,0.0001684466,0.9667758,0.000002010853,0.00001727104,0.000009623214,0.0003414268,0.003112262,0.0000421873,0.02635212,0.002683079,0.00009551647],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.926185,0.004267865,0.04134533,0.000222026,0.0009434171,0.0004912763,0.0000595074,0.00007805996,0.02640748],"genre_scores_gemma":[0.8821273,0.00007188856,0.117414,0.0001703391,0.00003399549,0.00001116088,0.00002185675,0.000001379993,0.0001480253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07606868,"threshold_uncertainty_score":0.9458504,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2901771398","doi":"10.1111/2041-210x.13133","title":"Past, present and future approaches using computer vision for animal re‐identification from camera trap data","year":2018,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":226,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Camera trap; Deep learning; Computer science; Artificial intelligence; Population; Data science; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.09820242396940591,"gpt":0.3602016114107164,"spread":0.2619991874413105,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001230666,0.00008160116,0.0001209207,0.00003866895,0.0002459282,0.00001559595,0.0001164347,0.0001941096,0.00004800032],"category_scores_gemma":[0.00002601396,0.00007971157,0.00001054769,0.00009137321,0.0003193259,0.0003510579,0.0001892417,0.00008793992,0.000004246258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006840102,"about_ca_system_score_gemma":0.000008371811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001410924,"about_ca_topic_score_gemma":0.0004682699,"domain_scores_codex":[0.9987735,0.0004123581,0.0001936161,0.0004266591,0.00004257767,0.0001513487],"domain_scores_gemma":[0.9994291,0.0002337131,0.00009128802,0.0002087517,0.000008189908,0.00002896815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001814734,0.0000789167,0.9275523,0.000007730657,0.00001351182,4.739697e-7,0.0004209547,0.00007920847,0.003766005,0.0001517794,0.00240129,0.0653464],"study_design_scores_gemma":[0.0002248211,0.0001134106,0.7092418,0.000002272532,0.00001872769,0.000003478516,0.00009219738,0.2859514,0.0000498405,0.002492195,0.001749279,0.00006060166],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7955284,0.00007035708,0.2018576,0.00191031,0.0003438141,0.0002384515,0.0000110484,0.0000104869,0.00002954497],"genre_scores_gemma":[0.6392958,0.00001327023,0.3596551,0.0001364582,0.0007999163,0.00001937285,0.00005886531,0.000004944808,0.00001631837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2858722,"threshold_uncertainty_score":0.3250543,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2897801176","doi":"10.1111/2041-210x.13159","title":"I can see clearly now: Reinterpreting statistical significance","year":2019,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":211,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"CLARITY; Null hypothesis; Statistical hypothesis testing; Meaning (existential); Alternative hypothesis; Psychology; Context (archaeology); Cognitive psychology; Computer science; Econometrics; Statistics; Mathematics; Geography; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.2100571163939553,"gpt":0.537255500117731,"spread":0.3271983837237757,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.009642188,0.0001654348,0.0006273185,0.0001040859,0.00006652711,0.00001728893,0.0001510012,0.0003427796,0.0005021446],"category_scores_gemma":[0.07395963,0.0001568813,0.0000473947,0.0001793517,0.0002724307,0.00005361922,0.0001166676,0.0005652343,0.00006834891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000176377,"about_ca_system_score_gemma":0.00006600303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003785643,"about_ca_topic_score_gemma":0.0001250461,"domain_scores_codex":[0.9935718,0.004606232,0.000777728,0.0005023089,0.0001282498,0.0004137064],"domain_scores_gemma":[0.9322332,0.06713937,0.0001903628,0.0002833738,0.00005810495,0.00009562015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003795144,0.0001741202,0.2337259,0.0002100623,0.00004964561,0.00001498606,0.0003046921,0.0000268375,0.003321353,0.7279707,0.0006818308,0.03314038],"study_design_scores_gemma":[0.0005472021,0.0002356306,0.1907427,0.00004446047,0.00002985518,0.000006079828,0.00009390026,0.004986249,0.0001787383,0.8028807,0.000102998,0.0001514585],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1563446,0.00002971905,0.8382403,0.0004927855,0.001161411,0.0005146993,0.00002713724,0.0000628725,0.003126455],"genre_scores_gemma":[0.3060703,0.00001158527,0.6933671,0.0001127187,0.00006438178,0.00003247334,7.592157e-7,0.00001631046,0.0003243427],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1497256,"threshold_uncertainty_score":0.9338408,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2003789729","doi":"10.1111/2041-210x.12226","title":"Body mass estimation in non‐avian bipeds using a theoretical conversion to quadruped stylopodial proportions","year":2014,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":203,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Tyrrell Museum; Royal Ontario Museum; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Circumference; Set (abstract data type); Estimation; Ecology; Biology; Mathematics; Statistics; Computer science; Engineering; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.01895620946374119,"gpt":0.3312692645166419,"spread":0.3123130550529007,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001737274,0.0001123164,0.0002297629,0.0003102424,0.0001900485,0.000007890325,0.00006846348,0.000198628,0.0005338461],"category_scores_gemma":[0.0007299549,0.0001031494,0.00002387714,0.0003243432,0.000324997,0.0001166515,0.00001421818,0.0001890467,0.00003341292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003291852,"about_ca_system_score_gemma":0.00003768687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006262056,"about_ca_topic_score_gemma":0.01718586,"domain_scores_codex":[0.9981251,0.0009498579,0.0002878634,0.0002701582,0.00007189698,0.0002950884],"domain_scores_gemma":[0.9992262,0.000506606,0.000065271,0.0000934353,0.00002964286,0.0000788855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008547912,0.00002248763,0.991677,0.00001140743,0.000005198394,0.000002945457,0.0003642761,0.001605775,0.00007883539,0.001801037,0.00002533019,0.004320181],"study_design_scores_gemma":[0.0002595758,0.0001326742,0.6687021,0.00001035663,0.00001007642,0.00000694619,0.000191819,0.3201083,0.00001267932,0.01044587,0.00003749704,0.00008215174],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7631001,0.00004843317,0.2331559,0.0003129043,0.000459769,0.0002613138,0.00001201891,0.00002187828,0.002627674],"genre_scores_gemma":[0.7809377,0.000008261546,0.2188731,0.0001140423,0.00002353224,0.000006100116,0.00002094354,0.000001648126,0.00001475904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.322975,"threshold_uncertainty_score":0.9590116,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2042238292","doi":"10.1111/j.2041-210x.2012.00244.x","title":"Do you hear what I hear? Implications of detector selection for acoustic monitoring of bats","year":2012,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Bat Biology and Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":195,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Human echolocation; Detector; SIGNAL (programming language); Acoustics; Bioacoustics; Selection (genetic algorithm); Detection theory; Physics; Computer science; Artificial intelligence; Optics","retraction":null,"screen_n_in":null,"score":{"opus":0.06048622084615762,"gpt":0.3575687222188388,"spread":0.2970825013726812,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001075581,0.0000698089,0.0002046267,0.0000283342,0.0001703895,0.000002728282,0.00005076348,0.0002318071,0.00001574679],"category_scores_gemma":[0.0003248463,0.00003531888,0.00003832609,0.0001750899,0.000147705,0.0001544086,0.00003474137,0.0000860156,7.063792e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003783899,"about_ca_system_score_gemma":0.000005354835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003278163,"about_ca_topic_score_gemma":0.0004014396,"domain_scores_codex":[0.9991591,0.0002597649,0.0001898425,0.0001401948,0.00001859882,0.000232502],"domain_scores_gemma":[0.9988186,0.0009661425,0.000101385,0.00002835415,0.00006155434,0.00002396574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003876786,0.00005596934,0.7793779,0.00001097625,0.00001404809,7.264847e-9,0.00007577716,0.000009166874,0.1999533,0.0001995791,0.00001393135,0.02025062],"study_design_scores_gemma":[0.000107452,0.0003185083,0.9886269,0.000008972615,0.0000244759,0.000004631786,0.0006327143,0.00005097119,0.008186202,0.001827111,0.0001566176,0.00005542516],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954903,0.001914565,0.001419084,0.0003992285,0.0005381139,0.0002027041,0.000006382582,0.00001135196,0.00001834147],"genre_scores_gemma":[0.9839646,0.0003440565,0.01544256,0.00001912816,0.0001243296,0.00008370305,0.000003365168,5.858316e-7,0.00001769415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.209249,"threshold_uncertainty_score":0.1787908,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2115993546","doi":"10.1111/2041-210x.12430","title":"An approach to estimate short‐term, long‐term and reaction norm repeatability","year":2015,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":180,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Volkswagen Foundation; Deutscher Akademischer Austauschdienst; International Max Planck Research School for Environmental, Cellular and Molecular Microbiology","keywords":"Repeatability; Multilevel model; Term (time); Phenotypic plasticity; Variation (astronomy); Regression; Contrast (vision); Scaling; Sample size determination; Statistics; Computer science; Econometrics; Biology; Ecology; Mathematics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.11770564100416,"gpt":0.3689078593342857,"spread":0.2512022183301257,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001209532,0.00008510053,0.0001581124,0.00001546462,0.0001380201,0.0000161049,0.00005442545,0.0001074147,0.000001637892],"category_scores_gemma":[0.0001460853,0.0000380796,0.0000128597,0.0001114101,0.00007575649,0.00014112,0.00006246656,0.00008871531,0.000001420276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004981222,"about_ca_system_score_gemma":0.000003643456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001359418,"about_ca_topic_score_gemma":0.004212277,"domain_scores_codex":[0.9991006,0.00026561,0.0001315586,0.0002816201,0.00004382496,0.0001768479],"domain_scores_gemma":[0.9997144,0.0001094722,0.00002505088,0.00002454199,0.00002808613,0.00009846339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007179767,0.00007288136,0.9058848,0.000004688412,0.000002841212,0.000001071168,0.0001194056,0.000002118846,0.04603422,0.00008820464,0.00001099782,0.04770698],"study_design_scores_gemma":[0.00007213444,0.0002891935,0.9979479,0.000003615748,0.000008042716,0.00002551039,0.000141651,0.0003279284,0.0001134073,0.0009126436,0.00006799906,0.00008997818],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982721,0.000152875,0.0005455335,0.0001364207,0.00007060236,0.0001380308,0.00000550769,0.00003144846,0.0006474416],"genre_scores_gemma":[0.9864953,0.00002727116,0.01331704,0.00003118444,0.00006874141,0.00002166458,0.00001661972,4.325132e-7,0.00002180312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09206311,"threshold_uncertainty_score":0.235055,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2151714956","doi":"10.1111/j.2041-210x.2011.00092.x","title":"Discriminating plant species in a local temperate flora using the <i>rbcL</i>+<i>matK</i> DNA barcode","year":2011,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":176,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto; University of British Columbia; University of Guelph","funders":"Ontario Genomics; University of Guelph; Ontario Genomics Institute; Genome Canada","keywords":"Barcode; DNA barcoding; Biology; Intergenic region; DNA sequencing; Locus (genetics); Botany; Evolutionary biology; Gene; Genetics; Genome; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.05615447322397591,"gpt":0.2815398985269256,"spread":0.2253854253029497,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009210113,0.0001189703,0.0001569177,0.00004602424,0.0002765923,0.000006214907,0.0001375358,0.00009145421,0.000154873],"category_scores_gemma":[0.0000692295,0.00009323801,0.00002223918,0.0001459954,0.0008918528,0.0001628283,0.0004186494,0.0001960308,0.00002169881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003913249,"about_ca_system_score_gemma":0.000002639301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009795459,"about_ca_topic_score_gemma":0.002148677,"domain_scores_codex":[0.99868,0.0004999925,0.000191705,0.0002639156,0.00008056303,0.0002838355],"domain_scores_gemma":[0.9996507,0.000148536,0.00005683196,0.000114845,0.000001450652,0.00002766853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002448471,0.00005836158,0.9827837,0.000005268374,0.000004679253,0.00000867922,0.00290104,0.0004737258,0.01266163,0.000130111,0.0000448655,0.0009033905],"study_design_scores_gemma":[0.0002246809,0.00004636375,0.9857343,0.00001079696,0.00001315398,0.00001621383,0.004759633,0.004616844,0.002820437,0.001541853,0.0001009184,0.0001147326],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858436,0.00008722871,0.01195545,0.00009256925,0.000177177,0.0001667364,0.000006431228,0.00001071176,0.001660086],"genre_scores_gemma":[0.8726622,0.00007006006,0.1270596,0.0001299887,0.00001019087,0.00001086636,0.000001366491,0.000004384233,0.00005140289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1151041,"threshold_uncertainty_score":0.3802136,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200562335","doi":"10.1111/2041-210x.13786","title":"Autocorrelation‐informed home range estimation: A review and practical guide","year":2021,"lang":"en","type":"review","venue":"Methods in Ecology and Evolution","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":175,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Estimator; Autocorrelation; Computer science; Kernel density estimation; Range (aeronautics); Sampling (signal processing); Sample (material); Home range; Statistics; Econometrics; Estimation; Data mining; Data science; Mathematics; Engineering; Telecommunications; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.060821639981071,"gpt":0.4364142897253212,"spread":0.3755926497442502,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002522293,0.0002202202,0.0009884024,0.00008727793,0.0001629571,0.00001259173,0.00006503865,0.0005985611,0.0007036604],"category_scores_gemma":[0.002641496,0.0002021168,0.00007677751,0.000389172,0.0002616709,0.0003164409,0.0001916365,0.0004702106,0.0001023528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004392592,"about_ca_system_score_gemma":0.0001926585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000233343,"about_ca_topic_score_gemma":0.0001825989,"domain_scores_codex":[0.9969764,0.0016354,0.0006639692,0.0004155166,0.00007707915,0.0002316472],"domain_scores_gemma":[0.997739,0.001666202,0.000321021,0.0001973873,0.0000134306,0.00006302702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004458397,0.00005834201,0.05209966,0.005622377,0.00004698949,0.00002084808,0.00004682921,0.00001412575,3.601223e-8,0.001414578,0.009477863,0.9311939],"study_design_scores_gemma":[0.0002177095,0.00005191921,0.2129296,0.002481483,0.0008033945,0.0005568599,0.000008500339,0.001031588,1.052484e-8,0.001700757,0.7799465,0.0002716615],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002890775,0.9818295,0.014766,0.0009687791,0.0003054617,0.0009351344,0.000002890198,0.00002528959,0.001138007],"genre_scores_gemma":[0.000001763009,0.8354988,0.1628988,0.0005615321,0.00002098025,0.0003722915,0.00004219114,0.000009103785,0.000594492],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9309222,"threshold_uncertainty_score":0.8242084,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2207744965","doi":"10.1111/2041-210x.12520","title":"The influence of environmental parameters on the performance and detection range of acoustic receivers","year":2015,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":171,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Becton Dickinson (Canada)","funders":"","keywords":"Environmental science; Range (aeronautics); Habitat; Telemetry; Hydrophone; Thermocline; Bioacoustics; Water column; Computer science; Ecology; Remote sensing; Geology; Oceanography; Telecommunications; Biology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01506772057507249,"gpt":0.2554492104632924,"spread":0.2403814898882199,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001373244,0.00004963161,0.00008005444,0.00002177075,0.0001500831,0.000001304243,0.00005989571,0.00004954431,0.000007607724],"category_scores_gemma":[0.0002502361,0.00003169938,0.000008311873,0.00006417244,0.0008396216,0.00006642504,0.00009617177,0.00008328298,0.000003011263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007437654,"about_ca_system_score_gemma":0.000002035512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003197425,"about_ca_topic_score_gemma":0.0005801216,"domain_scores_codex":[0.9993345,0.0003017477,0.0001136687,0.0001025009,0.00004910433,0.00009853661],"domain_scores_gemma":[0.9993147,0.0005188191,0.0000757798,0.00007597171,0.000002071001,0.00001267068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009056631,0.0000231317,0.9846132,0.000005300151,0.00001046416,1.838596e-7,0.0003685533,0.008451113,0.001436472,0.00004638816,0.00007867285,0.004875923],"study_design_scores_gemma":[0.0001879495,0.0002433149,0.9950659,0.000003027889,0.00001382522,0.000001424145,0.0005839228,0.00240131,0.0003385462,0.001067132,0.00006233752,0.00003132847],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987825,0.00003070894,0.0003689906,0.0001950853,0.00008003173,0.000150545,6.142171e-7,0.000002697896,0.0003888823],"genre_scores_gemma":[0.9982538,0.000351885,0.001254192,0.00007248086,0.000001788602,0.00002148659,8.236555e-8,0.000001515991,0.00004273349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01045265,"threshold_uncertainty_score":0.3093621,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1480001838","doi":"10.1111/j.2041-210x.2011.00174.x","title":"A comparative study of ecological specialization estimators","year":2012,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":170,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Rimouski","funders":"Centre National de la Recherche Scientifique; Ministère de l'Education Nationale, de l'Enseignement Superieur et de la Recherche; Agence Nationale de la Recherche","keywords":"Robustness (evolution); Generalist and specialist species; Estimator; Ecology; Population; Biological data; Computer science; Econometrics; Statistics; Mathematics; Biology; Bioinformatics; Habitat","retraction":null,"screen_n_in":null,"score":{"opus":0.1340806794696462,"gpt":0.3721099786169184,"spread":0.2380292991472722,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006065575,0.00005591575,0.0001891921,0.00001390836,0.00009750488,0.00000245909,0.00003621414,0.00006586276,0.00004242725],"category_scores_gemma":[0.00009501855,0.00002244522,0.00001302504,0.0001582834,0.00005890782,0.00006348345,0.00004329395,0.00005473481,0.000002363431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000205599,"about_ca_system_score_gemma":0.000001423058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006050164,"about_ca_topic_score_gemma":0.003367455,"domain_scores_codex":[0.9991878,0.0004008739,0.0001431358,0.00009333182,0.00003447965,0.0001404216],"domain_scores_gemma":[0.9995063,0.0003886516,0.0000578756,0.000007229988,0.0000164131,0.00002350788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002793941,0.0004589031,0.9882931,0.00000137347,0.000006519072,2.904529e-7,0.0005495437,0.000005175704,0.008101712,0.0007436054,0.00002652734,0.001785341],"study_design_scores_gemma":[0.0001155769,0.0004404118,0.9959568,0.000001834462,0.000008678561,0.000002233136,0.002195,0.0001452762,0.0001308718,0.0008222273,0.0001326619,0.00004844203],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989654,0.0001699423,0.0000883233,0.00003168241,0.00008496776,0.0001472713,0.000001972451,0.00001019405,0.0005002748],"genre_scores_gemma":[0.997386,0.00001539813,0.002497014,0.000009936838,0.00006426644,0.00001353383,0.000001990109,1.456333e-7,0.0000117442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007970841,"threshold_uncertainty_score":0.1879119,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2581099241","doi":"10.1111/2041-210x.12736","title":"paco: implementing Procrustean Approach to Cophylogeny in R","year":2017,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":167,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Cégep Marie-Victorin","funders":"Royal Society Te Apārangi; Royal Society; Generalitat Valenciana; University of Canterbury","keywords":"Phylogenetic tree; Congruence (geometry); Extant taxon; Systematics; Taxon; Biogeography; Concordance; Ecology; Evolutionary biology; Biology; Phylogenetics; Coevolution; Taxonomy (biology); Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.09373724982704977,"gpt":0.3458193680024788,"spread":0.252082118175429,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001077731,0.00006375839,0.0001377203,0.00001617584,0.0003910817,0.00002230333,0.000114478,0.00006970012,0.000008279539],"category_scores_gemma":[0.0002411597,0.00002795915,0.00001519155,0.00006788362,0.00004709545,0.00005931018,0.0001582327,0.00008312908,0.000003005983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002728633,"about_ca_system_score_gemma":0.000002500781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003867166,"about_ca_topic_score_gemma":0.01509447,"domain_scores_codex":[0.999258,0.0001479491,0.000124189,0.000190496,0.00002935208,0.0002500387],"domain_scores_gemma":[0.9997767,0.0001141948,0.00005246768,0.00001905724,0.00001041418,0.00002711864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001947146,0.00003540398,0.9314339,0.00000448837,0.000002230615,0.000001182829,0.00008135752,0.000001438872,0.03478901,0.0006714549,0.00004841614,0.03291167],"study_design_scores_gemma":[0.00009986501,0.00007781893,0.9959423,0.00000518246,0.000002218956,0.000002851557,0.0003432398,0.0001818341,0.0001537775,0.00189466,0.001226497,0.00006974354],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943599,0.00008901448,0.0001025558,0.0004029504,0.00004728008,0.0001551703,0.000003981992,0.000008812353,0.00483035],"genre_scores_gemma":[0.9863604,0.00002859974,0.01337695,0.00005513958,0.00006076867,0.00003319587,0.000002185092,2.816229e-7,0.00008249326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06450843,"threshold_uncertainty_score":0.842307,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1606496075","doi":"10.1111/j.2041-210x.2012.00209.x","title":"Field test of an affordable, portable, wireless microphone array for spatial monitoring of animal ecology and behaviour","year":2012,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Animal Vocal Communication and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":163,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Algoma University; University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Ontario; University of Windsor","keywords":"Microphone; Computer science; Loudspeaker; Microphone array; Global Positioning System; Position (finance); Wireless; Geographic coordinate system; Real-time computing; Acoustics; Telecommunications; Sound pressure; Geography; Cartography","retraction":null,"screen_n_in":null,"score":{"opus":0.02874381242354895,"gpt":0.3629033614379961,"spread":0.3341595490144472,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000667691,0.00008349341,0.0001921979,0.00005237511,0.00005682977,0.000001977806,0.0000776882,0.0002670368,0.00000584692],"category_scores_gemma":[0.0001897318,0.00008507365,0.00002718891,0.00004676907,0.0001233946,0.00001066688,0.00006242537,0.00008894403,1.00965e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001298572,"about_ca_system_score_gemma":0.00002696104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001282296,"about_ca_topic_score_gemma":0.0002542271,"domain_scores_codex":[0.9992304,0.0001782637,0.000239914,0.0001450268,0.00002409212,0.0001822901],"domain_scores_gemma":[0.9994931,0.0001350151,0.0001249211,0.000140783,0.00005902671,0.00004715495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000145505,0.0001371284,0.4965731,0.00001317226,0.000003722799,6.578846e-8,0.00002852198,3.216508e-7,0.5009582,0.00001913678,0.0000032056,0.002117898],"study_design_scores_gemma":[0.0002711062,0.001160421,0.5791326,0.000003701942,0.00001999292,0.000006807063,0.0001236752,0.00002182729,0.4191395,0.00003534003,0.00003371681,0.00005125404],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762956,0.0004546501,0.02287622,0.00003053624,0.0001386073,0.0001598598,0.00001141971,0.000002999787,0.0000300932],"genre_scores_gemma":[0.8533256,0.00009989012,0.1464224,0.00001473095,0.00005877741,0.0000306531,0.00001616452,0.000006540633,0.00002529218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1235461,"threshold_uncertainty_score":0.3469203,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2066586787","doi":"10.1111/2041-210x.12020","title":"Avoiding fishy growth curves","year":2013,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":158,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Indeterminate growth; Statistics; Growth curve (statistics); Growth rate; Logarithm; Biology; Mathematics; Extinction (optical mineralogy); Equivalence (formal languages); Econometrics; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.01384988161376038,"gpt":0.2869604814359843,"spread":0.273110599822224,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001287229,0.00006993087,0.000117793,0.00004187706,0.0002478548,0.000003967458,0.00006898127,0.0000809782,0.00130682],"category_scores_gemma":[0.0005593995,0.00006570403,0.00001358807,0.0001269839,0.00021965,0.0002154685,0.0002052314,0.0001700571,0.0002167141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008390152,"about_ca_system_score_gemma":0.000001726512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000211831,"about_ca_topic_score_gemma":0.001168239,"domain_scores_codex":[0.998898,0.0005422101,0.0001243809,0.0001953231,0.00003249651,0.0002075902],"domain_scores_gemma":[0.9995627,0.0003128594,0.00003680536,0.00006051964,0.000004270126,0.00002283191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002398998,0.000027967,0.9667524,0.00001724201,0.000006413384,0.000001193634,0.00008440562,0.00001516532,0.0001678212,0.0008103531,0.03066684,0.001447854],"study_design_scores_gemma":[0.0001242995,0.00003455072,0.9614955,0.000007608058,0.000008110158,0.000003509051,0.0001149815,0.0005293707,0.00003866902,0.03704736,0.0005254912,0.00007057674],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9203979,0.000336655,0.02010554,0.00652788,0.0004612545,0.0004632146,4.646445e-7,0.00005605071,0.05165099],"genre_scores_gemma":[0.9564772,0.000719313,0.03956423,0.002132525,0.00001380886,0.0001363785,0.000001211143,0.000004027185,0.0009513616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05069963,"threshold_uncertainty_score":0.9996061,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2900774961","doi":"10.1111/2041-210x.13126","title":"Expanding the role of social science in conservation through an engagement with philosophy, methodology, and methods","year":2019,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Environmental Philosophy and Ethics","field":"Environmental Science","cited_by":153,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University; University of British Columbia","funders":"","keywords":"Data science; Objectivism; Qualitative research; Epistemology; Management science; Set (abstract data type); Social research; Perspective (graphical); Value (mathematics); Field (mathematics); Computer science; Sociology; Social science; Engineering ethics; Artificial intelligence; Engineering; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.07006228955471994,"gpt":0.3929907597942266,"spread":0.3229284702395067,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01009755,0.0001068332,0.0002073332,0.00007240031,0.0002467794,0.000007683763,0.0001506077,0.0001421244,0.00006926685],"category_scores_gemma":[0.0001882266,0.00008114795,0.00001357346,0.00034319,0.001898062,0.0005287725,0.0002332937,0.0003436242,0.000002267489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001785981,"about_ca_system_score_gemma":0.00001602063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002406252,"about_ca_topic_score_gemma":0.0001554474,"domain_scores_codex":[0.9963421,0.002726263,0.0002290681,0.0003557598,0.0001222396,0.000224535],"domain_scores_gemma":[0.9988138,0.0008950678,0.0001156031,0.0001447205,0.000005315941,0.00002549007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009331363,0.00007136259,0.8267107,0.00001333231,0.00000461376,4.601134e-7,0.005526485,0.0002965514,0.1091668,0.0499079,6.334105e-7,0.008207859],"study_design_scores_gemma":[0.0003115964,0.0001842064,0.7291687,0.000006603495,0.000009272481,0.000005583389,0.001870703,0.00128427,0.005248201,0.2617485,0.00008161882,0.00008071748],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.974288,0.00009443965,0.01694354,0.0007549183,0.00009447007,0.0003078521,9.403719e-7,0.000007102407,0.007508742],"genre_scores_gemma":[0.6787863,0.00003316966,0.3209566,0.0001845519,0.000009935377,0.00001836968,7.832087e-7,0.00000400586,0.000006298609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3040131,"threshold_uncertainty_score":0.6993487,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4318191119","doi":"10.1111/2041-210x.14060","title":"aniMotum, an R package for animal movement data: Rapid quality control, behavioural estimation and simulation","year":2023,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":140,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Office of Naval Research; Fisheries and Oceans Canada; Natural Environment Research Council; Commonwealth Scientific and Industrial Research Organisation; Centre National d’Etudes Spatiales; Bundesministerium für Bildung und Forschung; Australian Research Council; Sight Research UK; UK Research and Innovation","keywords":"Computer science; Workflow; Inference; Data quality; Data mining; Quality (philosophy); Noise (video); Data science; Tracking (education); Real-time computing; Machine learning; Artificial intelligence; Database","retraction":null,"screen_n_in":null,"score":{"opus":0.1555840281180648,"gpt":0.4426248669702682,"spread":0.2870408388522034,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002439623,0.00008227721,0.0001370888,0.00004261806,0.0001722177,0.0000185541,0.0000756978,0.0001061842,0.0004618869],"category_scores_gemma":[0.0003323538,0.00008341881,0.00001327504,0.0001427652,0.0001337473,0.0003813503,0.0001115661,0.00006175448,0.00001468847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002321237,"about_ca_system_score_gemma":0.000004602871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001495035,"about_ca_topic_score_gemma":0.001059775,"domain_scores_codex":[0.998828,0.0003725667,0.0002151196,0.0003097146,0.00007050179,0.0002041321],"domain_scores_gemma":[0.9993569,0.000340516,0.00007577433,0.0001676171,0.000009132953,0.00005001203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002094159,0.0001160773,0.9553854,0.0000201568,0.00000684398,0.000001033274,0.0002481901,0.001593683,0.01342532,0.002218637,0.0003497783,0.02642541],"study_design_scores_gemma":[0.0006127706,0.0001386582,0.7182676,0.000001211644,0.0000116626,5.865151e-7,0.0003817105,0.2778812,0.00006736755,0.002466518,0.0001033342,0.00006745245],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9112578,0.00002676161,0.08764425,0.0003393127,0.0001285672,0.00032503,0.0001595543,0.00004347491,0.00007523733],"genre_scores_gemma":[0.9877731,0.00002423358,0.01153289,0.0001213733,0.00001422173,0.000048046,0.0004588804,0.000005080202,0.00002214917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2762875,"threshold_uncertainty_score":0.5057338,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2609102980","doi":"10.1111/2041-210x.12799","title":"Spatio‐temporal connectivity: assessing the amount of reachable habitat in dynamic landscapes","year":2017,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":136,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Ministerio de Economía y Competitividad","keywords":"Habitat; Biological dispersal; Landscape connectivity; Ecology; Spatial heterogeneity; Temporal scales; Geography; Biology; Population","retraction":null,"screen_n_in":null,"score":{"opus":0.02073264027981828,"gpt":0.3583715022497256,"spread":0.3376388619699073,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001516622,0.00005415927,0.000113821,0.00003696778,0.0002298069,0.00002368501,0.00009316781,0.00007259793,0.00004838858],"category_scores_gemma":[0.0004263212,0.0000431514,0.00001588863,0.00006466328,0.0001735353,0.0004134338,0.00008084996,0.0001287621,0.000003877906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001697806,"about_ca_system_score_gemma":0.00001304563,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003570556,"about_ca_topic_score_gemma":0.06191611,"domain_scores_codex":[0.9991679,0.0003715229,0.0001624453,0.0001426403,0.00004353463,0.0001119698],"domain_scores_gemma":[0.999373,0.0002835648,0.0001553031,0.0001706917,0.000006355017,0.00001114219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001174796,0.00003750278,0.9905946,0.000003162753,0.000002203383,6.674419e-7,0.0001106872,0.0003989925,0.001325539,0.0002213912,0.00002898146,0.00726455],"study_design_scores_gemma":[0.0001792211,0.00003061154,0.92915,0.0000116009,0.000004517434,0.000004614061,0.0001901582,0.06354237,0.00007874726,0.006569728,0.0001947381,0.0000437281],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881457,0.0000289371,0.00900693,0.00106733,0.0001878817,0.0001037478,7.629313e-7,0.000004571438,0.00145412],"genre_scores_gemma":[0.9842575,0.00001104211,0.01559596,0.00003972974,0.00000718658,0.00002140442,0.000001789221,0.000002795426,0.00006265349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06314338,"threshold_uncertainty_score":0.9552015,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2132360826","doi":"10.1111/2041-210x.12106","title":"Calibrating indices of avian density from non‐standardized survey data: making the most of a messy situation","year":2013,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":135,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; Alberta Biodiversity Monitoring Institute; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Fish and Wildlife Service","keywords":"Breeding bird survey; Sampling (signal processing); Covariate; Songbird; Range (aeronautics); Statistics; Survey data collection; RADIUS; Count data; Ecology; Geography; Environmental science; Mathematics; Habitat; Computer science; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.04222651582612921,"gpt":0.3494875924357468,"spread":0.3072610766096177,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002761524,0.00007227415,0.0002080706,0.00003327311,0.0001306355,0.000005193848,0.0001955396,0.0001637185,0.0003542999],"category_scores_gemma":[0.0005977796,0.00005570713,0.00001334321,0.0001844656,0.0004254965,0.0003011925,0.0002919892,0.0001491665,0.000006585359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005978586,"about_ca_system_score_gemma":0.00001988196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00301739,"about_ca_topic_score_gemma":0.01713329,"domain_scores_codex":[0.9980022,0.001278667,0.0002873713,0.0002189288,0.00007365811,0.0001391532],"domain_scores_gemma":[0.9985983,0.0009040705,0.0002360982,0.0002294528,0.00001465253,0.00001741589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000271875,0.00003847571,0.9849294,0.000003426483,0.000007790278,4.40186e-7,0.0005339134,0.00008759901,0.008628572,0.000005920109,0.00006227208,0.005674967],"study_design_scores_gemma":[0.0002489567,0.00003851813,0.9908577,0.000007550403,0.00002576021,0.000001548044,0.0002900411,0.005288514,0.001295937,0.001888098,0.000002960784,0.00005447662],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9488807,0.00003151942,0.05055074,0.00006503162,0.0001235284,0.0002181348,0.0000296331,0.000004724568,0.0000959899],"genre_scores_gemma":[0.9267462,0.000006004347,0.07314089,0.00004051929,0.000008498198,0.00001218831,0.00003069873,0.000003258203,0.00001173595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02259015,"threshold_uncertainty_score":0.9560781,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2889761511","doi":"10.1111/2041-210x.13166","title":"Tracktor: Image‐based automated tracking of animal movement and behaviour","year":2019,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":134,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"California Department of Fish and Game","keywords":"Computer science; Computer vision; Software; Source code; Artificial intelligence; Tracking (education); Kinematics; Video tracking; Robustness (evolution); Workflow; Graphical user interface; Tracking system; Coding (social sciences); Data mining; Object (grammar); Database; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.02766866746713774,"gpt":0.3434378039048974,"spread":0.3157691364377596,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006537332,0.0000688347,0.0001329201,0.00003881159,0.00004070006,0.000005840668,0.00004226078,0.00009438011,0.003912917],"category_scores_gemma":[0.00004433994,0.00006816674,0.00001797867,0.0001066441,0.0001549038,0.0001007577,0.00005069254,0.00007240538,0.00002530255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002250211,"about_ca_system_score_gemma":0.000005177253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001143585,"about_ca_topic_score_gemma":0.000197262,"domain_scores_codex":[0.9992693,0.0001732459,0.0001654611,0.0001782701,0.00005933511,0.000154387],"domain_scores_gemma":[0.9997473,0.00007536038,0.00006610579,0.00007345442,0.000006672436,0.00003112806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003489767,0.00007224312,0.8613195,0.00001102659,0.000001803318,8.301158e-7,0.00007711576,0.00001464323,0.1372973,0.0002515789,0.00007441319,0.0008446187],"study_design_scores_gemma":[0.0004876281,0.000166666,0.98357,0.000004470058,0.000008511932,0.000002324564,0.0004599236,0.009040642,0.005931137,0.0001940017,0.00006614591,0.00006849654],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972652,0.0000468811,0.0008675279,0.000119826,0.0000919171,0.0001481194,0.00001067898,0.00003196888,0.001417834],"genre_scores_gemma":[0.9871725,0.00001311315,0.01268712,0.00007604752,0.000002978147,0.00001015387,0.000007432468,0.000003649729,0.00002698678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1313662,"threshold_uncertainty_score":0.9969977,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2781561787","doi":"10.1111/2041-210x.12962","title":"Field methods for sampling tree height for tropical forest biomass estimation","year":2018,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Forest ecology and management","field":"Environmental Science","cited_by":134,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"FP7 Ideas: European Research Council; Seventh Framework Programme; Ministerstvo Školství, Mládeže a Tělovýchovy; European Commission; David and Lucile Packard Foundation; Sight Research UK; Agence Nationale Des Parcs Nationaux; Royal Geographical Society; Royal Society; Gordon and Betty Moore Foundation; Leverhulme Trust; Wildlife Conservation Society; Natural Environment Research Council","keywords":"Biomass (ecology); Sampling (signal processing); Environmental science; Field (mathematics); Tree (set theory); Tropical forest; Ecology; Forestry; Statistics; Soil science; Remote sensing; Mathematics; Geography; Biology; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.03436651014473612,"gpt":0.3976483355070315,"spread":0.3632818253622954,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001586527,0.00009734499,0.0001679992,0.0000736974,0.0002541014,0.000007463864,0.00009720165,0.0002235819,0.0001104844],"category_scores_gemma":[0.001020749,0.00009129864,0.00004286327,0.0001131593,0.0002494559,0.0001185451,0.00009557077,0.00007058134,0.00001086521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001426227,"about_ca_system_score_gemma":0.000007517113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004048532,"about_ca_topic_score_gemma":0.002785567,"domain_scores_codex":[0.9988825,0.000281904,0.0002209628,0.0003007422,0.00002755461,0.0002863889],"domain_scores_gemma":[0.9984171,0.001346271,0.00006936138,0.0001191937,0.00001055905,0.00003748727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007350976,0.0001973878,0.5106158,0.00007828247,0.00004514276,6.476664e-7,0.0003043301,0.0006938896,0.002759074,0.1049217,0.003146073,0.3765026],"study_design_scores_gemma":[0.0005024856,0.0006649314,0.5966623,0.000002939781,0.00002448423,0.000002353032,0.00001886702,0.1179269,0.0007966766,0.2764829,0.006830499,0.00008458751],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09151369,0.00003050324,0.9059363,0.0006779872,0.0005986004,0.0005724542,0.000001283055,0.00002124519,0.0006479363],"genre_scores_gemma":[0.2386631,0.000004178522,0.7606194,0.0002128755,0.00005490123,0.0002871642,0.000005249777,0.000005612458,0.0001475178],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.376418,"threshold_uncertainty_score":0.3723051,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1996773798","doi":"10.1111/2041-210x.12111","title":"Phylogenetic eigenvector maps: a framework to model and predict species traits","year":2013,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":133,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Phylogenetic tree; Trait; Phylogenetics; Evolutionary biology; Biology; Phylogenetic comparative methods; Tree (set theory); Phylogenetic network; Set (abstract data type); Computer science; Mathematics; Genetics; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.03131917815586251,"gpt":0.2967698468201589,"spread":0.2654506686642964,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005215349,0.0001255762,0.000225738,0.0001467908,0.0001880902,0.00001457503,0.00007397008,0.0002045209,0.000286089],"category_scores_gemma":[0.0003492595,0.0001092303,0.00001977779,0.0001659926,0.0002470723,0.00009090736,0.00002092409,0.0001812146,0.00004970238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009605985,"about_ca_system_score_gemma":0.00002219473,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003276781,"about_ca_topic_score_gemma":0.01956469,"domain_scores_codex":[0.9987743,0.0003661762,0.0001976295,0.0002925667,0.00005584303,0.0003134698],"domain_scores_gemma":[0.9992508,0.0004942471,0.00003825567,0.00007879414,0.0000279455,0.0001099411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000018834,0.000009990578,0.984504,0.00001123538,0.00001315087,8.816024e-7,0.0005094246,0.001768486,0.0001221818,0.0007193297,0.0003993616,0.01192308],"study_design_scores_gemma":[0.0001460762,0.000137625,0.925529,0.00000891289,0.00001136801,0.00001117093,0.0002420094,0.03266199,0.00000489369,0.04092371,0.0002105419,0.0001127033],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.950158,0.003156622,0.04164987,0.001044036,0.0002916536,0.0003291423,0.00002143233,0.00003090947,0.003318333],"genre_scores_gemma":[0.7779008,0.0002223612,0.2211424,0.0004080947,0.00004725514,0.0000157932,0.000003556557,0.000001787022,0.0002579575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1794925,"threshold_uncertainty_score":0.9983257,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3005825300","doi":"10.1111/2041-210x.13349","title":"Operationalizing ecological connectivity in spatial conservation planning with Marxan Connect","year":2020,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":132,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Queensland; University of Leeds; University of Melbourne; Centre of Excellence for Environmental Decisions, Australian Research Council","keywords":"Computer science; Operationalization; Landscape connectivity; Environmental resource management; Ecology; Geography; Biological dispersal; Environmental science; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.03719736691774362,"gpt":0.3237609615918702,"spread":0.2865635946741266,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007343109,0.00008988014,0.0001508384,0.00004723226,0.0001181093,0.00001490161,0.00004969137,0.0001132421,0.0003476056],"category_scores_gemma":[0.0004927061,0.00008241556,0.00001234133,0.0002305296,0.000118576,0.000291785,0.00005518807,0.0002050306,0.00001254439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002099453,"about_ca_system_score_gemma":0.0000208846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001013948,"about_ca_topic_score_gemma":0.005388437,"domain_scores_codex":[0.9987068,0.0005799701,0.0002102442,0.0002835618,0.00006190901,0.0001575776],"domain_scores_gemma":[0.9993637,0.0004637246,0.00006900451,0.00005340753,0.000009757684,0.0000403593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001316064,0.00005182945,0.9852894,0.000004472768,0.000002892862,0.000007002764,0.0003127693,0.008085781,0.003616297,0.0006032009,0.00008220183,0.001812574],"study_design_scores_gemma":[0.0004939548,0.0002036182,0.8790426,0.000008325804,0.000004617993,0.00001193445,0.0002141665,0.1186932,0.0001482871,0.0007555475,0.0003281353,0.00009570571],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9034273,0.00001098586,0.09180573,0.003662318,0.00007511643,0.0001910408,0.000001093794,0.00001923403,0.0008072075],"genre_scores_gemma":[0.9642971,0.000003240733,0.0339762,0.00162038,0.0000258787,0.00005242793,0.000008011627,0.000004341226,0.00001244855],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1106074,"threshold_uncertainty_score":0.3806037,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2115087711","doi":"10.1111/2041-210x.12470","title":"Multipurpose habitat networks for short‐range and long‐range connectivity: a new method combining graph and circuit connectivity","year":2015,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":130,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Compute Canada","keywords":"Habitat; Range (aeronautics); Landscape connectivity; Habitat fragmentation; Biodiversity; Geography; Ecology; Fragmentation (computing); Environmental resource management; Environmental science; Biology; Biological dispersal; Population","retraction":null,"screen_n_in":null,"score":{"opus":0.05490769614589549,"gpt":0.3491697562721681,"spread":0.2942620601262726,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00274129,0.0001558006,0.0002898664,0.00009607058,0.000208855,0.00003034075,0.00005434564,0.0002173094,0.00001761406],"category_scores_gemma":[0.0007134228,0.0001600511,0.00003326727,0.0001989023,0.0002137279,0.0004236658,0.0001051851,0.0002164782,0.000001388244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001664955,"about_ca_system_score_gemma":0.00002033203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00104608,"about_ca_topic_score_gemma":0.008893546,"domain_scores_codex":[0.9982265,0.0007718708,0.000225306,0.0004359423,0.00006547049,0.0002749284],"domain_scores_gemma":[0.9981189,0.001502974,0.00008325301,0.0001268706,0.0000218082,0.0001461507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001220081,0.00006357757,0.9264708,0.000009060158,0.00001688533,0.000001905054,0.0004808541,0.0005624694,0.0002983348,0.0006190008,0.0002962725,0.07105888],"study_design_scores_gemma":[0.001109819,0.0002683074,0.8727468,0.0000124179,0.00004285464,0.00005946807,0.0002575518,0.1032024,0.00002331127,0.02171275,0.0003969538,0.0001673243],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5199143,0.0002916227,0.4788368,0.0002632081,0.0002115457,0.0003354115,0.000002071492,0.00001886002,0.0001262155],"genre_scores_gemma":[0.8800266,0.0000510529,0.1194383,0.0002432871,0.00004353945,0.0001170293,0.000004161869,0.0000111471,0.00006479924],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3601124,"threshold_uncertainty_score":0.6526694,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2396688143","doi":"10.1111/2041-210x.12597","title":"State‐and‐transition simulation models: a framework for forecasting landscape change","year":2016,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":130,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Centre For Cold Ocean Resources Engineering; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Forest Service; U.S. Geological Survey; Nature Conservancy of Canada; Nature Conservancy; Ontario Ministry of Natural Resources and Forestry; Ministry of Natural Resources","keywords":"Markov chain; Land cover; Land use, land-use change and forestry; Computer science; Land use; Econometrics; Mathematics; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.07211151204608941,"gpt":0.3332683102666896,"spread":0.2611567982206002,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007811324,0.00006410483,0.0001046288,0.0000367041,0.00009880248,0.000006056991,0.00002886782,0.0001170714,0.0000589575],"category_scores_gemma":[0.00006185638,0.00004434045,0.00001363183,0.00006295532,0.00001757989,0.0003298412,0.00002958949,0.00003848083,0.000005585925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005133686,"about_ca_system_score_gemma":0.000001983591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006450634,"about_ca_topic_score_gemma":0.0009183317,"domain_scores_codex":[0.9993508,0.0001354447,0.0001294756,0.0001837028,0.00003242043,0.0001681614],"domain_scores_gemma":[0.9993196,0.0005444558,0.00004858609,0.00005299913,0.000005291786,0.00002912888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002839598,0.00006256323,0.7185645,0.0001211176,0.00001609012,0.000001754262,0.00356915,0.04130279,0.000596121,0.001555863,0.0000134797,0.2339126],"study_design_scores_gemma":[0.0003210111,0.00006969962,0.1671194,0.0000342922,0.000007901792,0.000002633119,0.00005121849,0.6368512,0.00002765299,0.195393,0.00005521972,0.00006682603],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5324306,0.00006395704,0.4670248,0.0001944691,0.00007093167,0.0001506647,0.000003416939,0.000008112404,0.00005306812],"genre_scores_gemma":[0.9089578,0.00005816808,0.09076772,0.0000798163,0.00004091245,0.000081955,0.00000175997,0.000004672614,0.000007154433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5955484,"threshold_uncertainty_score":0.1808151,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2116300154","doi":"10.1111/2041-210x.12188","title":"Synchrony: quantifying variability in space and time","year":2014,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Animal Ecology and Behavior Studies","field":"Environmental Science","cited_by":129,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Univariate; Bivariate analysis; Computer science; Nonparametric statistics; Autocorrelation; Spatial analysis; Multivariate statistics; Data mining; Parametric statistics; Independence (probability theory); Temporal database; Bivariate data; Statistics; Machine learning; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.02347070801337084,"gpt":0.341023394854952,"spread":0.3175526868415812,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003893353,0.0000734553,0.0001708246,0.00003699908,0.0001129649,0.000002847355,0.00004019867,0.0001530186,0.0002023589],"category_scores_gemma":[0.0006051009,0.00006962819,0.000009732843,0.0001041968,0.0003930768,0.00008473494,0.0001516084,0.0001545593,0.00003285455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001316764,"about_ca_system_score_gemma":0.00000389342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001664429,"about_ca_topic_score_gemma":0.001143633,"domain_scores_codex":[0.9983164,0.00107145,0.0001364378,0.0002583312,0.00002673267,0.0001906175],"domain_scores_gemma":[0.999225,0.0006444157,0.00003425781,0.00006970782,0.000002189021,0.00002439433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001716313,0.0000432632,0.9873457,0.000004973575,0.000001352214,0.000001067742,0.0001513967,0.00003561356,0.003000387,0.002264042,0.00002071304,0.007114328],"study_design_scores_gemma":[0.0002071319,0.0000876629,0.9768988,0.000003154144,0.000007600204,0.000005917659,0.00004609992,0.007615258,0.0000550957,0.01485043,0.0001497319,0.00007308392],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839829,0.00004697749,0.01191515,0.0002756621,0.00008255463,0.0001006798,3.147292e-7,0.00001184167,0.003583925],"genre_scores_gemma":[0.9473575,0.00002010817,0.05246434,0.00004683394,0.000007048337,0.00001605447,3.526793e-7,0.000002534586,0.00008518126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0405492,"threshold_uncertainty_score":0.2839355,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2105500189","doi":"10.1111/2041-210x.12454","title":"Owl pellets: a more effective alternative to conventional trapping for broad‐scale studies of small mammal communities","year":2015,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Animal Ecology and Behavior Studies","field":"Environmental Science","cited_by":128,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Saskatchewan Museum; University of Regina","funders":"Canada Research Chairs; University of Regina","keywords":"Species richness; Habitat; Pellets; Species evenness; Dominance (genetics); Mammal; Ecology; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.1001334370586507,"gpt":0.4102129003722588,"spread":0.310079463313608,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001456985,0.00009539952,0.0002646129,0.00006387133,0.0001549647,0.000001771931,0.0000816207,0.00008983877,0.00002816938],"category_scores_gemma":[0.0003001714,0.00008774015,0.00003681328,0.0000932531,0.0007234797,0.00006156691,0.0002025609,0.0001082134,0.000006405368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00021826,"about_ca_system_score_gemma":0.000009354654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002347119,"about_ca_topic_score_gemma":0.005935591,"domain_scores_codex":[0.9989287,0.0005043313,0.0001888031,0.0001529235,0.00004713937,0.0001780535],"domain_scores_gemma":[0.9990051,0.0007826673,0.00007583226,0.0000614083,0.00003853302,0.00003646506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003483045,0.0001467317,0.9780371,0.00002454832,0.00005965603,9.486362e-7,0.01386988,0.0007869435,0.001166077,0.0004018077,0.0003310514,0.004827],"study_design_scores_gemma":[0.0007811175,0.0006525377,0.9753787,0.00001638918,0.00004073133,0.000006190048,0.0137597,0.0006047693,0.0003565575,0.007864723,0.0004409189,0.00009765755],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9629422,0.0002645003,0.03545076,0.0003252855,0.0002270455,0.0004647247,0.000008652946,0.000008621163,0.000308163],"genre_scores_gemma":[0.8825001,0.00002575846,0.1168721,0.00009330849,0.00001697666,0.0002922638,0.000003022,0.000004166041,0.0001922849],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08142135,"threshold_uncertainty_score":0.357794,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2513563772","doi":"10.1111/2041-210x.12641","title":"Testing and recommending methods for fitting size spectra to data","year":2016,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":126,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria; Fisheries and Oceans Canada","funders":"Natural Environment Research Council; Natural Sciences and Engineering Research Council of Canada; Department for Environment, Food and Rural Affairs, UK Government","keywords":"Groundfish; Statistics; Environmental science; Mathematics; Remote sensing; Ecology; Geography; Biology; Fishing","retraction":null,"screen_n_in":null,"score":{"opus":0.08506838933723697,"gpt":0.4045414502784833,"spread":0.3194730609412463,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005775394,0.00008472679,0.0001490486,0.00004426411,0.0002143416,0.000007414558,0.0001318364,0.0001275626,0.0001083313],"category_scores_gemma":[0.01168591,0.00007038562,0.000008761988,0.0001627692,0.0001133021,0.0002514263,0.0003304842,0.00008009767,0.000006959746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001351819,"about_ca_system_score_gemma":0.000009996955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005936358,"about_ca_topic_score_gemma":0.0003004544,"domain_scores_codex":[0.9984111,0.0006932127,0.000211664,0.0004045494,0.00002292923,0.000256584],"domain_scores_gemma":[0.9910346,0.008654255,0.00007321958,0.0001808424,0.000006326444,0.00005075857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002047014,0.00001040669,0.7187104,0.000003754381,0.000003356541,2.769166e-7,0.00005291183,0.000004684962,0.01426216,0.0001531452,0.0002914605,0.2664869],"study_design_scores_gemma":[0.0003221309,0.0001013565,0.9618471,0.00001351831,0.00001227597,0.00001234931,0.00004412229,0.006299611,0.0002467546,0.02960852,0.001393765,0.00009851532],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4292769,0.00002884546,0.5661819,0.003522474,0.0002456877,0.0002472994,0.000003492639,0.00002155663,0.0004718796],"genre_scores_gemma":[0.1210669,0.000008395697,0.8781938,0.0005141829,0.00003987983,0.00004848253,0.000001088695,0.000005767979,0.0001215145],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3120119,"threshold_uncertainty_score":0.9966391,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}