{"id":"W4399091579","doi":"10.1332/policypress/9781447365624.002.0007","title":"Preface","year":2023,"lang":"en","type":"book-chapter","venue":"Policy Press eBooks","topic":"Historical Studies on Reproduction, Gender, Health, and Societal Changes","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001327062,0.0003859178,0.0004718736,0.00011957,0.0007949974,0.00009195741,0.000248838,0.0002208324,0.0002534998],"category_scores_gemma":[0.00003138868,0.000351603,0.0002554664,0.000003926275,0.0004559544,0.00003135873,0.000153944,0.0004254816,0.0004546713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002623214,"about_ca_system_score_gemma":0.0001149888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005415713,"about_ca_topic_score_gemma":0.001690855,"domain_scores_codex":[0.998247,0.00002222538,0.0003535762,0.000560508,0.0003738311,0.0004428553],"domain_scores_gemma":[0.9989294,0.000061345,0.000194379,0.0005011544,0.0001553852,0.0001582871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006070712,0.000006033338,8.047045e-8,0.00021509,0.0001147311,0.000003104971,0.04898319,3.043256e-7,3.100861e-7,0.8163822,0.1305577,0.00373115],"study_design_scores_gemma":[0.0000949812,0.00005453143,9.813845e-7,0.00004753148,0.00005324789,0.000001251131,0.0003161265,7.813819e-7,0.000004109828,0.02988718,0.9691952,0.0003440186],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000003088304,0.002296669,0.000001356002,0.000650018,0.001935983,0.0004163755,0.0002176768,0.0004938568,0.993985],"genre_scores_gemma":[0.0001381628,0.001758733,0.000005948597,0.0005878821,0.01186223,0.00007696381,0.00002320096,0.0001363843,0.9854105],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8386375,"threshold_uncertainty_score":0.9998936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2350917285163795,"score_gpt":0.306027613854409,"score_spread":0.07093588533802955,"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."}}