{"id":"W1485657404","doi":"10.4000/belphegor.603","title":"La fiction d’affaires, une source pour l’histoire du temps présent","year":2015,"lang":"fr","type":"article","venue":"Belphégor","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Art","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":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002314333,0.0003316199,0.0002790734,0.00007939699,0.0002940033,0.001213169,0.0004780413,0.0002297523,0.00004899845],"category_scores_gemma":[0.0002152761,0.0002652317,0.0001554014,0.0005543505,0.0002608059,0.002250688,0.0003533128,0.0002586092,0.0008913883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002870267,"about_ca_system_score_gemma":0.0003637753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004523524,"about_ca_topic_score_gemma":0.0003884738,"domain_scores_codex":[0.9979159,0.0001546821,0.0003647842,0.000515622,0.0005040165,0.0005450309],"domain_scores_gemma":[0.9982541,0.00008496136,0.0001764681,0.0005093798,0.0003104586,0.0006645859],"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":[0.00002742741,0.0004807769,0.0001098073,0.0000493656,0.00003096349,0.0003699634,0.009133582,0.0004453802,0.0002218918,0.09095986,0.6814777,0.2166933],"study_design_scores_gemma":[0.0007582594,0.000231853,0.0009021046,0.0001232228,0.00002911809,0.0009897718,0.000987476,0.01229147,0.0002584244,0.002765507,0.9802629,0.000399917],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01967396,0.01653589,0.02565499,0.06753202,0.00748956,0.0004865515,0.00002919272,0.0005393305,0.8620585],"genre_scores_gemma":[0.7466044,0.00009659648,0.001511176,0.0007781744,0.001086089,0.000009872962,0.00001566278,0.00002940749,0.2498687],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7269304,"threshold_uncertainty_score":0.99998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1491004598167223,"score_gpt":0.285577508530529,"score_spread":0.1364770487138067,"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."}}