{"id":"W4240627121","doi":"10.1515/iupac.88.1289","title":"Rete Testis","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Testicular diseases and treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.001215519,0.001029274,0.001517733,0.00397484,0.0007011998,0.002789129,0.001996948,0.001596248,0.1369752],"category_scores_gemma":[0.01429815,0.0005337839,0.001865247,0.006688696,0.0003967216,0.001914831,0.00210014,0.00170145,0.09604574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001320327,"about_ca_system_score_gemma":0.003539812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01452448,"about_ca_topic_score_gemma":0.03088055,"domain_scores_codex":[0.9985456,0.0002536986,0.000383763,0.0003728903,0.0002862738,0.0001577668],"domain_scores_gemma":[0.9946185,0.001675613,0.0009554106,0.001025268,0.001403417,0.0003219049],"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":[0.0001403582,0.000009870172,0.002246386,0.003491428,0.00007877045,0.00004971976,0.0000273774,0.000142453,0.00009002906,0.0009667583,0.9802077,0.01254902],"study_design_scores_gemma":[0.0001719582,0.00001663622,0.005622135,0.002431913,0.00007607669,0.0002167519,0.00005436048,0.000100576,0.0001578101,0.001465796,0.9896615,0.00002448448],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001498733,0.0007327384,0.0001309324,0.0002051636,0.00008614564,0.00004224183,0.9954795,0.0002067865,0.00296671],"genre_scores_gemma":[0.001026364,0.0009960725,0.0006145597,0.0005739969,0.00006541995,0.0002180994,0.9938434,0.0001071788,0.002554837],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1369752,"threshold_uncertainty_score":0.4582276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02162468750668913,"score_gpt":0.4530831119412288,"score_spread":0.4314584244345397,"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."}}