{"id":"W4392409487","doi":"10.62212/revuepossibles.v47i2.725","title":"Trouver des portes de sortie : à partir des futurités noires","year":2023,"lang":"fr","type":"article","venue":"Revue Possibles","topic":"Social Sciences and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political 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":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.001074382,0.0002300002,0.0003224066,0.00007052896,0.001615449,0.0002736819,0.0005533115,0.0002495901,0.0007211229],"category_scores_gemma":[0.0005122215,0.0002414344,0.0002571508,0.002294485,0.003043289,0.0007238822,0.0001083607,0.0001878161,0.0006320465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003368714,"about_ca_system_score_gemma":0.0005032399,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03175936,"about_ca_topic_score_gemma":0.07059702,"domain_scores_codex":[0.9971082,0.0002475482,0.0003708867,0.0004510537,0.0004667824,0.001355567],"domain_scores_gemma":[0.9987671,0.0003083678,0.0002188182,0.0002165405,0.0001096248,0.0003795329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00001891734,0.0001642799,0.3143623,0.0004240267,0.00007530775,0.0001572305,0.124465,0.0002784055,0.0003077906,0.03972184,0.1001818,0.4198432],"study_design_scores_gemma":[0.0002545385,0.0001286846,0.5833758,0.000723556,0.0001100621,0.00001333552,0.03465934,0.0006568618,0.0003879062,0.142747,0.2363036,0.000639294],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9463792,0.02719393,0.00005055426,0.0147289,0.001824868,0.0001742292,0.00007781995,0.0002351747,0.00933535],"genre_scores_gemma":[0.8920436,0.03128491,0.0009990004,0.0002209623,0.002837229,0.00004088258,0.000006331169,0.00002703485,0.07254004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4192039,"threshold_uncertainty_score":0.9996843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08832942751028615,"score_gpt":0.3453386409826837,"score_spread":0.2570092134723975,"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."}}