{"id":"W4415045598","doi":"10.7202/1118944ar","title":"L’écrivain et la machine","year":2024,"lang":"fr","type":"article","venue":"Sens public","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Order (exchange); Work (physics); Point (geometry); Set (abstract data type)","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003730048,0.0002279567,0.000165078,0.0001397374,0.00008777528,0.01116488,0.0003754818,0.0001295927,0.0003227986],"category_scores_gemma":[0.0001694577,0.0001657246,0.0001355335,0.0008411022,0.0001455836,0.004914478,0.0003833642,0.0003595388,0.001631903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005223856,"about_ca_system_score_gemma":0.0002447469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004495723,"about_ca_topic_score_gemma":0.0001384013,"domain_scores_codex":[0.9983846,0.0001530597,0.0002100375,0.0004446831,0.0002826022,0.0005249991],"domain_scores_gemma":[0.9988689,0.0002490448,0.0000282829,0.000401724,0.00009915101,0.0003528732],"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":[5.835641e-7,0.0000590115,0.000006837572,0.00005157613,0.00003208502,0.0008118447,0.001870379,0.000006106662,0.0001503374,0.7777678,0.1155857,0.1036578],"study_design_scores_gemma":[0.00008593789,0.0000673649,0.0003178293,0.0001279703,0.000009025593,0.001185563,0.00002263381,0.02989123,0.00009713213,0.02315864,0.9447997,0.0002369303],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.002936331,0.02936892,0.008138124,0.2711267,0.00480844,0.0001195144,0.00007045312,0.0005210409,0.6829105],"genre_scores_gemma":[0.7192143,0.0002882992,0.001037146,0.004563721,0.0005009719,0.00000214057,0.00002734438,0.00002433851,0.2743417],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.829214,"threshold_uncertainty_score":0.9991454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2398526069463507,"score_gpt":0.3458613886450089,"score_spread":0.1060087816986582,"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."}}