{"id":"W4365147715","doi":"10.1515/iupac.94.0532","title":"Homo","year":2023,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Terminology; Meaning (existential); Abandonment (legal); Field (mathematics); Epistemology; Computer science; Linguistics; Philosophy; Mathematics; Political science","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":[0.001099024,0.002332802,0.001330117,0.003585631,0.001332938,0.00343601,0.002591275,0.001904627,0.2636167],"category_scores_gemma":[0.006629625,0.0006354547,0.001569075,0.004662457,0.0004946339,0.003013203,0.002889157,0.001913672,0.4101384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001320787,"about_ca_system_score_gemma":0.002074341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0168302,"about_ca_topic_score_gemma":0.03563366,"domain_scores_codex":[0.9983031,0.0002965774,0.0002075758,0.0006292408,0.0003358282,0.0002277045],"domain_scores_gemma":[0.9974979,0.000546838,0.0001968594,0.0009125213,0.0006707617,0.0001750316],"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":[0.00004707578,0.00001276559,0.0003299979,0.0003724608,0.00001148545,0.00001379282,0.00001862388,0.0000601043,0.00009271906,0.0005407043,0.994795,0.003705137],"study_design_scores_gemma":[0.00007648886,0.00001301515,0.001809275,0.0003089603,0.00001342542,0.0000663254,0.00007626343,0.0001738119,0.0002028189,0.001672038,0.9955645,0.00002302786],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001181118,0.0001036961,0.0001454284,0.00009384954,0.00005103825,0.00002156437,0.9959888,0.0006742561,0.002803293],"genre_scores_gemma":[0.0002327199,0.00006508992,0.0003029999,0.0001339635,0.00001076915,0.00007572701,0.9975721,0.0001216283,0.001485015],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2636167,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01761771028084874,"score_gpt":0.4060411302527786,"score_spread":0.3884234199719299,"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."}}