{"id":"W4232892662","doi":"10.1002/9781119096276.index","title":"Index","year":2016,"lang":"en","type":"paratext","venue":"Advances in chemical physics","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Library science; Index (typography); Engineering physics; Engineering; Computer 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00004382907,0.0006126918,0.0006916696,0.00002825001,0.00005558829,0.00001745166,0.0008262621,0.0006359057,0.01148597],"category_scores_gemma":[0.00006312989,0.0005659731,0.0002010687,0.0001610664,0.0003841248,0.0003812514,0.0002251521,0.001153046,0.002818781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006235262,"about_ca_system_score_gemma":0.0001228576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001502005,"about_ca_topic_score_gemma":5.839788e-7,"domain_scores_codex":[0.9974107,0.000009597969,0.0005723152,0.0009144499,0.0004392468,0.0006536685],"domain_scores_gemma":[0.9983894,0.0002289861,0.0003524635,0.0008271856,0.00005701707,0.0001449572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002153657,0.0006894542,0.0001599255,0.004660631,0.0001037209,0.00005817078,0.00009366102,0.0003340316,0.5938678,0.0004676106,0.1405638,0.2587858],"study_design_scores_gemma":[0.0004960617,0.000002527347,4.887722e-8,0.0007377262,0.000009067223,0.000001823215,0.000007602167,0.000005726609,0.3156814,0.00505469,0.6774763,0.0005270274],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0006975186,0.01121185,0.0009175002,0.00002573909,0.001375093,0.0000658015,0.0004183873,0.00007015248,0.9852179],"genre_scores_gemma":[0.1085196,0.02223104,0.001461098,0.0005103889,0.01383978,0.0004169106,0.001870519,0.0004600215,0.8506906],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5369125,"threshold_uncertainty_score":0.9996791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01020562210324832,"score_gpt":0.2869509381274311,"score_spread":0.2767453160241827,"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."}}