{"id":"W4205696440","doi":"10.7202/1079759ar","title":"De machine fictionnelle à machine de guerre. Général Instin","year":2021,"lang":"fr","type":"article","venue":"Captures","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Art; Suite; History; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0001447986,0.0002693583,0.0002432227,0.00004919875,0.0002491323,0.001481832,0.0003875509,0.0001846089,0.00067403],"category_scores_gemma":[0.0002944389,0.0002291944,0.0001813119,0.0004141588,0.0001321608,0.001133754,0.0003482534,0.0003729862,0.0001475937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001473159,"about_ca_system_score_gemma":0.0003268268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003207954,"about_ca_topic_score_gemma":0.001214418,"domain_scores_codex":[0.9982874,0.0001247731,0.0002626657,0.0004322695,0.0002239158,0.0006689996],"domain_scores_gemma":[0.9987596,0.0000895516,0.00008222594,0.0004471529,0.0001622024,0.000459292],"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":[0.00004370574,0.0008230323,0.002262723,0.0002060226,0.0001768655,0.005811178,0.0167699,0.0086381,0.01307103,0.6245703,0.2173383,0.1102888],"study_design_scores_gemma":[0.0009136044,0.0001700543,0.01672035,0.0002395156,0.00006738241,0.005447036,0.0003176951,0.1097563,0.01847079,0.05451818,0.7926064,0.0007727476],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09717777,0.2027283,0.1089331,0.04921301,0.008042946,0.0003103739,0.000267626,0.0004786809,0.5328481],"genre_scores_gemma":[0.8737546,0.0003472728,0.005876514,0.006449115,0.0007675676,0.00000483829,0.00005731998,0.00002162574,0.1127212],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7765768,"threshold_uncertainty_score":0.9995548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1219444346686288,"score_gpt":0.2910061991093283,"score_spread":0.1690617644406995,"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."}}