{"id":"W3210720616","doi":"","title":"Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning","year":2021,"lang":"en","type":"article","venue":"Neural Information Processing Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Probabilistic logic; Scalability; Deductive reasoning; Deductive database; Database; Programming language; Natural language processing; Artificial intelligence; Data mining; Information retrieval","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":[0.001823385,0.0009863193,0.001053942,0.001099827,0.0005882063,0.002965106,0.004321215,0.0009789407,0.01683164],"category_scores_gemma":[0.01282066,0.001095769,0.001581509,0.001530093,0.001404472,0.005978822,0.005029846,0.003228532,0.003979304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001184913,"about_ca_system_score_gemma":0.001838388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005939442,"about_ca_topic_score_gemma":0.01088646,"domain_scores_codex":[0.9985169,0.0002552931,0.0001326238,0.000323862,0.0006679471,0.0001034906],"domain_scores_gemma":[0.9952582,0.002182256,0.0001583658,0.001806686,0.0004839152,0.0001106162],"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":[0.0006470546,0.0002608831,0.001637056,0.0008050962,0.000252573,0.0002790776,0.0002444783,0.113588,0.00516576,0.1392672,0.06062228,0.6772305],"study_design_scores_gemma":[0.00008570826,0.0000346555,0.0002371137,0.00005039542,0.00006174235,0.00006539477,0.00004052755,0.7682598,0.005635294,0.2129534,0.0125527,0.00002327759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006876859,0.0004784867,0.9575413,0.0005356405,0.0001278783,0.0001131623,0.001547152,0.02885566,0.003923723],"genre_scores_gemma":[0.195883,0.0006662249,0.7892269,0.0006355368,0.0001453623,0.0002376572,0.004321263,0.003182869,0.005701165],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01683164,"threshold_uncertainty_score":0.05630744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02153156765752779,"score_gpt":0.2609899767663771,"score_spread":0.2394584091088493,"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."}}