{"id":"W4205756477","doi":"10.4000/books.pubp.3410","title":"De l’anticipation dystopique chez Nelly Arcan","year":2019,"lang":"fr","type":"book-chapter","venue":"Presses universitaires Blaise-Pascal eBooks","topic":"French Historical and Cultural Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Anticipation (artificial intelligence); Psychology; History; Computer science; Artificial intelligence","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","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001059089,0.0007875247,0.0007959012,0.000164478,0.001377956,0.0002615461,0.0005871656,0.0004739274,0.006369964],"category_scores_gemma":[0.00003030342,0.000724531,0.0005344691,0.00001704829,0.001572994,0.0002445713,0.0003297933,0.000707365,0.0007162091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006649743,"about_ca_system_score_gemma":0.000250608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002835133,"about_ca_topic_score_gemma":0.002281917,"domain_scores_codex":[0.9975054,0.00009396125,0.0004739577,0.000724811,0.0004656126,0.0007362732],"domain_scores_gemma":[0.9983294,0.0002279957,0.0003646207,0.0004184531,0.0003583187,0.000301186],"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":[0.0001182858,0.00006537107,0.00005511515,0.0005517312,0.0005229961,0.0001322236,0.006189977,0.00006098963,0.0001391954,0.9638156,0.01312111,0.01522739],"study_design_scores_gemma":[0.0005058508,0.0003905929,0.0001894917,0.0006617011,0.0007195537,0.00001199713,0.0008865601,0.0001111146,0.0001527502,0.01604681,0.9793895,0.0009339988],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0016062,0.006939901,0.0001128558,0.002365137,0.001377924,0.0005856489,0.0002203978,0.0002166343,0.9865753],"genre_scores_gemma":[0.2737146,0.00062838,0.00005702068,0.0001927086,0.001018606,0.00000813564,0.00008167102,0.00006699,0.7242319],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9662685,"threshold_uncertainty_score":0.9999221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02622849385144812,"score_gpt":0.1914515115358655,"score_spread":0.1652230176844173,"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."}}