{"id":"W2000760706","doi":"10.3166/ria.18.261-298","title":"Programmation bayésienne des robots","year":2004,"lang":"fr","type":"article","venue":"Revue d intelligence artificielle","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008655319,0.0003960821,0.0003687765,0.0001597197,0.0005895039,0.0006440814,0.001127895,0.0002664153,0.0004124232],"category_scores_gemma":[0.0004122901,0.0004103523,0.0002634836,0.001499187,0.0006629608,0.001200002,0.0003310265,0.0003882225,0.007453329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003568549,"about_ca_system_score_gemma":0.0002997214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003787607,"about_ca_topic_score_gemma":0.0003168337,"domain_scores_codex":[0.9967999,0.0001431511,0.0007402611,0.0009020582,0.000296282,0.001118383],"domain_scores_gemma":[0.9977856,0.0001528796,0.0002463255,0.0009638966,0.0004776037,0.0003737207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007505007,0.0005606928,0.0001616413,0.0001970695,0.00002083334,0.0000824353,0.01104172,0.08492047,0.0005445273,0.4539504,0.000231421,0.4482813],"study_design_scores_gemma":[0.0002384064,0.0009860757,0.0005217211,0.001564388,0.00007108553,0.0006539911,0.001437159,0.5302625,0.09709749,0.3008889,0.06508976,0.001188446],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01378976,0.01426071,0.9365289,0.004214946,0.003020143,0.0005525032,0.000003376564,0.0002888836,0.02734083],"genre_scores_gemma":[0.9093807,0.001350038,0.05690424,0.000162652,0.0007142814,0.00006394363,0.00001105262,0.00004305781,0.03137007],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8955909,"threshold_uncertainty_score":0.9998348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06938033144524185,"score_gpt":0.2833472566051876,"score_spread":0.2139669251599458,"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."}}