{"id":"W4244148016","doi":"10.1515/iupac.87.0439","title":"Neurogenesis","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Medical and Biological Sciences","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Psychology; Neuroscience; Cognitive science; Chemistry; Linguistics; Philosophy; Data mining; Organic chemistry","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":[0.001070651,0.001447108,0.001259533,0.003229172,0.0009976912,0.003613485,0.002346206,0.001733349,0.1417525],"category_scores_gemma":[0.009734527,0.0005343413,0.001689587,0.004925534,0.0003750074,0.002128896,0.001979856,0.001619645,0.1535271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001423916,"about_ca_system_score_gemma":0.002736469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01258462,"about_ca_topic_score_gemma":0.02554734,"domain_scores_codex":[0.9983121,0.0002443469,0.000328731,0.0005500018,0.0003595164,0.0002052695],"domain_scores_gemma":[0.9965718,0.0008652375,0.000379826,0.0008588768,0.001068742,0.0002555389],"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":[0.0001714203,0.00001848336,0.002460676,0.001313183,0.00004152332,0.00003711688,0.0000375607,0.0001764338,0.0001037962,0.001242224,0.98239,0.01200747],"study_design_scores_gemma":[0.0001219826,0.00001604492,0.003611255,0.0005291521,0.00003230227,0.0001065517,0.00007593595,0.0001368742,0.0001956374,0.00164115,0.9935154,0.00001774159],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002442685,0.0003080596,0.0001448616,0.0001877593,0.00009460128,0.00003090758,0.9945287,0.0004207769,0.004039995],"genre_scores_gemma":[0.0008593556,0.000318471,0.0005715888,0.000309767,0.00002702296,0.000116898,0.9947096,0.00009682019,0.00299051],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1417525,"threshold_uncertainty_score":0.4742092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02946585030394996,"score_gpt":0.4236462685078695,"score_spread":0.3941804182039195,"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."}}