{"id":"W4393797638","doi":"10.5281/zenodo.8305892","title":"GBIF records for Krajewski et al. 2023","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Ottawa","funders":"","keywords":"Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007109244,0.0018243,0.00124274,0.004720174,0.0006904806,0.00205545,0.002366236,0.00169129,0.04075255],"category_scores_gemma":[0.003521669,0.0006882426,0.001539936,0.005718256,0.0004711894,0.001364511,0.001483883,0.001812346,0.08437191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001282929,"about_ca_system_score_gemma":0.002176021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02790437,"about_ca_topic_score_gemma":0.05836979,"domain_scores_codex":[0.9993091,0.00007289642,0.0001106166,0.00021439,0.0001626259,0.0001304125],"domain_scores_gemma":[0.9989337,0.0001552221,0.0001413656,0.0003469135,0.0002925503,0.000130245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000957931,0.00002618488,0.001327025,0.0006875579,0.00004462642,0.00005077698,0.00003783236,0.0002785664,0.000283052,0.0004837048,0.9928908,0.003793982],"study_design_scores_gemma":[0.0001367244,0.00001561006,0.00769766,0.0002747908,0.00003697645,0.0001704585,0.0001221634,0.0004020182,0.0005158397,0.0009011268,0.9896961,0.00003043297],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003821877,0.0001259956,0.0001249412,0.00005504578,0.00003520857,0.00001420335,0.9978034,0.0005843507,0.0008747808],"genre_scores_gemma":[0.0004201534,0.00006254804,0.0002861426,0.00002433535,0.000005513666,0.00003979832,0.9985014,0.0000946997,0.0005653353],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04075255,"threshold_uncertainty_score":0.1363309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06808853524158524,"score_gpt":0.3466127776570472,"score_spread":0.2785242424154619,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}