{"id":"W4411141319","doi":"10.1145/3725250","title":"Smallest Synthetic Witnesses for Conjunctive Queries","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Universitas Brawijaya","keywords":"Conjunctive query; Computer science; Information retrieval; Relational database","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":[0.004020431,0.0008595621,0.001367024,0.0008886742,0.001081945,0.003187925,0.002167635,0.001437684,0.007455106],"category_scores_gemma":[0.02483471,0.0007734019,0.001584535,0.001491578,0.001520767,0.01071285,0.004040366,0.002093174,0.0008187562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001215059,"about_ca_system_score_gemma":0.001468727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009988025,"about_ca_topic_score_gemma":0.001493088,"domain_scores_codex":[0.9950676,0.0009177409,0.0006559367,0.001470382,0.001471563,0.0004166955],"domain_scores_gemma":[0.981984,0.01209021,0.001313778,0.00304089,0.001016252,0.0005548978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.004327036,0.0008808787,0.01579568,0.003210411,0.000586007,0.001174752,0.003803917,0.1259838,0.06883511,0.356698,0.02492024,0.3937841],"study_design_scores_gemma":[0.0004019359,0.0004683236,0.002008405,0.000151919,0.0001996635,0.0009720423,0.001399521,0.5079336,0.04656733,0.4245609,0.01524769,0.00008871698],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2338613,0.001030061,0.7444987,0.003600675,0.0001313919,0.0008121167,0.0048771,0.003692457,0.007496172],"genre_scores_gemma":[0.590995,0.0003445956,0.3972062,0.0005603964,0.000147233,0.0004115448,0.00641402,0.0005747877,0.00334617],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007455106,"threshold_uncertainty_score":0.02493984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2317777557871395,"score_gpt":0.4214874451748175,"score_spread":0.1897096893876779,"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."}}