{"id":"W2613944953","doi":"","title":"Types for REWERSE reasoning and query languages I3-D4","year":2005,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Prevention of Organ Failure","funders":"","keywords":"Computer science; Artificial intelligence; Natural language processing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01664609,0.001665817,0.002283901,0.003186745,0.002939792,0.01241526,0.00668223,0.005931274,0.02123433],"category_scores_gemma":[0.03271066,0.00396752,0.005522379,0.00499639,0.007534757,0.03249335,0.006638968,0.01774982,0.004104361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007456513,"about_ca_system_score_gemma":0.003442845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009335847,"about_ca_topic_score_gemma":0.005044184,"domain_scores_codex":[0.9808647,0.006257841,0.002579568,0.002456035,0.006215039,0.001626803],"domain_scores_gemma":[0.9651249,0.01929075,0.001113928,0.007708556,0.00589106,0.0008707746],"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":[0.00005455485,0.00003359851,0.0003489233,0.0002460459,0.00002736321,0.00009544571,0.0007801728,0.001655321,0.0007552081,0.9755329,0.00680499,0.01366537],"study_design_scores_gemma":[0.0000367664,0.00002511846,0.0002815204,0.0001495576,0.00004657777,0.0001441621,0.0003092449,0.008631511,0.001783236,0.9546727,0.03386399,0.00005547385],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003981362,0.002068173,0.9677711,0.008930087,0.0007757233,0.000135416,0.0004978951,0.00184948,0.01399062],"genre_scores_gemma":[0.2193844,0.004200779,0.7164081,0.008829853,0.003422304,0.0008691458,0.002695292,0.003240365,0.04094973],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02123433,"threshold_uncertainty_score":0.08803397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01582523575379233,"score_gpt":0.2532818451922444,"score_spread":0.2374566094384521,"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."}}