{"id":"W4394715462","doi":"10.62212/revuepossibles.v43i1.110","title":"Equipe METISS","year":2019,"lang":"fr","type":"article","venue":"Revue Possibles","topic":"Migration, Identity, and Health","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer 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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007490958,0.0001359746,0.0002802764,0.00008779405,0.0004433314,0.0001679641,0.0002845033,0.0001982115,0.006186698],"category_scores_gemma":[0.00007040308,0.0001520184,0.0001281254,0.0005266152,0.0002025115,0.0004569177,0.00004704352,0.0001636601,0.00774808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001811261,"about_ca_system_score_gemma":0.0003602657,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01037422,"about_ca_topic_score_gemma":0.02190308,"domain_scores_codex":[0.9983785,0.0002129569,0.0003092211,0.0003041504,0.0002925477,0.0005026293],"domain_scores_gemma":[0.9991362,0.0001057859,0.0001529985,0.0002682268,0.000120458,0.0002163302],"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":[0.00001227754,0.0001616594,0.2021754,0.001539978,0.00004445922,0.000008763484,0.03119689,0.00002879586,0.0001607655,0.6976238,0.05012991,0.0169173],"study_design_scores_gemma":[0.000340561,0.0001748001,0.06095598,0.0005913377,0.00009886947,0.0000111996,0.004184407,0.0002299417,0.00009341853,0.06905107,0.8638097,0.0004586744],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7157556,0.05967135,0.00008135498,0.02433756,0.008245142,0.0005154745,0.00004809614,0.0000818298,0.1912636],"genre_scores_gemma":[0.6404869,0.03230553,0.0005367254,0.000456886,0.002289287,0.000008060079,0.0000162775,0.00001694789,0.3238834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8136798,"threshold_uncertainty_score":0.9962158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04246955062195216,"score_gpt":0.3378738916593764,"score_spread":0.2954043410374242,"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."}}