{"id":"W4392021732","doi":"10.51644/9780889205383-004","title":"Table 1: Subject Classification Codes (headings listed alphabetically in English) / Tableau 1: Codification de la classification par thèmes (matières en anglais par ordre alphabétique)","year":2010,"lang":"fr","type":"book-chapter","venue":"","topic":"Medical and Biological Sciences","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Table (database); Subject (documents); Computer science; Humanities; Information retrieval; Library science; Art; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001787983,0.001319733,0.001157495,0.0124693,0.002094446,0.003696091,0.001188261,0.000694501,0.4601939],"category_scores_gemma":[0.01188813,0.0004437014,0.0005061641,0.02668803,0.001122169,0.002354563,0.001467459,0.001674288,0.3006526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007306419,"about_ca_system_score_gemma":0.01517398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1446886,"about_ca_topic_score_gemma":0.129157,"domain_scores_codex":[0.9971642,0.0003437403,0.0004521175,0.0003451387,0.0014068,0.0002880619],"domain_scores_gemma":[0.9842324,0.002522122,0.000705934,0.0006281566,0.01117026,0.0007410696],"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":[0.00003278673,0.00001547765,0.0004507636,0.0007311453,0.000003003171,0.00003318064,0.0004732136,0.0000535925,0.0004010964,0.006172158,0.966248,0.02538555],"study_design_scores_gemma":[0.000009673592,0.000009442469,0.002678849,0.0002962789,0.000003203194,0.00004035252,0.0004569989,0.00004006546,0.0001691232,0.001087973,0.9951977,0.00001041073],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001947949,0.001678554,0.00397948,0.003147495,0.004327059,0.003096922,0.5270038,0.00166744,0.4531513],"genre_scores_gemma":[0.009123121,0.004208327,0.01719823,0.001281479,0.0009882997,0.003472567,0.3990502,0.002347531,0.5623304],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.4601939,"threshold_uncertainty_score":0.7699679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03120442376913074,"score_gpt":0.2869252072622129,"score_spread":0.2557207834930821,"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."}}