{"id":"W4392326348","doi":"10.51644/9780889206304-004","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":2006,"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; Linguistics; Library science; Philosophy; Database","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":[0.00178886,0.001336109,0.001190726,0.0126909,0.001991217,0.003582908,0.001178287,0.0006850822,0.4559492],"category_scores_gemma":[0.01186308,0.0004419539,0.0005023341,0.02704415,0.001075724,0.002276559,0.001409776,0.001650467,0.295758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006898907,"about_ca_system_score_gemma":0.01446806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1347318,"about_ca_topic_score_gemma":0.119789,"domain_scores_codex":[0.997183,0.000345185,0.0004733673,0.0003384117,0.001378256,0.0002818804],"domain_scores_gemma":[0.983895,0.002560321,0.0007590879,0.0006439578,0.0113823,0.0007592393],"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":[0.00003470766,0.00001662179,0.0004822522,0.0007447063,0.000003117767,0.0000343251,0.0004572723,0.00005553742,0.0004187938,0.005717122,0.966054,0.02598151],"study_design_scores_gemma":[0.00001098009,0.00001086754,0.003131049,0.0003045575,0.00000348253,0.0000439179,0.0004637983,0.0000453561,0.0001818861,0.001119628,0.9946731,0.00001139469],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001998246,0.001663885,0.004111854,0.003092101,0.00434299,0.003293514,0.5618623,0.001716205,0.4179189],"genre_scores_gemma":[0.009166114,0.004137516,0.01841628,0.001259953,0.0009831437,0.003705142,0.4220127,0.002298258,0.5380209],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.4559492,"threshold_uncertainty_score":0.7760224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03036191768815035,"score_gpt":0.280189700380483,"score_spread":0.2498277826923326,"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."}}