{"id":"W1571851487","doi":"10.1007/978-3-540-73580-9_5","title":"Partial Pattern Databases","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Reduction (mathematics); Abstraction; Heuristic; Database; Table (database); Parallel computing; Theoretical computer science; Artificial intelligence; Mathematics","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":[0.0005564958,0.000727826,0.0009721984,0.001636142,0.0006956062,0.003691648,0.001691261,0.0006103293,0.04741982],"category_scores_gemma":[0.002353043,0.0006984643,0.0007926785,0.003804006,0.0004688031,0.00532615,0.001723109,0.0009999222,0.02307288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005106701,"about_ca_system_score_gemma":0.0008517734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001085234,"about_ca_topic_score_gemma":0.001431016,"domain_scores_codex":[0.9993176,0.00007412046,0.00008923377,0.0001838254,0.0002954942,0.00003972964],"domain_scores_gemma":[0.999087,0.0001438347,0.00002849771,0.0005372931,0.000162987,0.00004044344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001372499,0.00007132922,0.0004824414,0.0003844521,0.00004927316,0.0001248393,0.0001338167,0.002192457,0.003143885,0.1679484,0.0951968,0.7301351],"study_design_scores_gemma":[0.00003685739,0.00005997425,0.0004477158,0.0001460117,0.00007082441,0.001084206,0.0001418409,0.01378457,0.009620814,0.2890471,0.6855314,0.00002872485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01117853,0.005469154,0.7656687,0.001622914,0.0007188385,0.0003474435,0.01425619,0.0149075,0.1858308],"genre_scores_gemma":[0.1333965,0.008008982,0.5464898,0.001025858,0.0003653632,0.0004820881,0.05364828,0.003139972,0.2534432],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04741982,"threshold_uncertainty_score":0.1586351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04454709949354994,"score_gpt":0.2802821028687497,"score_spread":0.2357350033751997,"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."}}