{"id":"W2275001223","doi":"10.1016/j.artint.2019.07.002","title":"The logic of qualitative probability","year":2019,"lang":"en","type":"article","venue":"Artificial Intelligence","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Interpretation (philosophy); Axiom; Operator (biology); Set (abstract data type); Outcome (game theory); Possibility theory; Axiomatic system; Finite set; Set theory; Mathematics; Binary operation; Modal operator; Domain (mathematical analysis); Infinite set; Probability theory; Computer science; Discrete mathematics; Theoretical computer science; Mathematical economics; Fuzzy set; Artificial intelligence; Multimodal logic; Fuzzy logic; Description logic; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007796035,0.0007294787,0.001122248,0.002805811,0.002185631,0.007052908,0.001876101,0.002556216,0.006564669],"category_scores_gemma":[0.01791807,0.0009601405,0.001502133,0.002590887,0.01957138,0.01255527,0.002141526,0.005488324,0.001054795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004961169,"about_ca_system_score_gemma":0.002315187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005110508,"about_ca_topic_score_gemma":0.002513665,"domain_scores_codex":[0.9948868,0.003177074,0.000269892,0.0006611123,0.0008363372,0.000168689],"domain_scores_gemma":[0.9882706,0.009051505,0.0004738557,0.001141932,0.0008430692,0.0002190459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000001724419,0.000001218835,0.000018332,0.00001057957,0.0000027075,0.000005623724,0.00005180015,0.0001977622,0.00001376397,0.9986313,0.0003338715,0.0007312376],"study_design_scores_gemma":[0.000002108889,7.478148e-7,0.0000114232,0.000007299503,0.000001767123,0.000005073331,0.00001037546,0.000609064,0.0000160386,0.9971347,0.002199505,0.000001879182],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008998129,0.01228245,0.8067087,0.03338358,0.0009810759,0.000100999,0.0007735536,0.0002632696,0.1365082],"genre_scores_gemma":[0.6795716,0.0114132,0.2742301,0.006691244,0.002862316,0.0006865569,0.000693028,0.0002177551,0.02363438],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007796035,"threshold_uncertainty_score":0.04122984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1938683637179671,"score_gpt":0.3876034118537989,"score_spread":0.1937350481358317,"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."}}