{"id":"W2142682193","doi":"10.1002/cjs.5550340109","title":"Optimally and computations for relative surprise inferences","year":2006,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Surprise; A priori and a posteriori; Mathematics; Humanities; Invariant (physics); Philosophy; Epistemology; Psychology; Mathematical physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.006935777,0.00125227,0.00181313,0.002352268,0.002252887,0.007525457,0.003429744,0.002576035,0.01904276],"category_scores_gemma":[0.06658325,0.001629829,0.002366501,0.002373316,0.00309829,0.01390183,0.005276709,0.004208958,0.003437744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003869922,"about_ca_system_score_gemma":0.002861222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004105347,"about_ca_topic_score_gemma":0.005110409,"domain_scores_codex":[0.9932307,0.00196288,0.0006116522,0.001697053,0.001717959,0.0007797224],"domain_scores_gemma":[0.9782515,0.01608949,0.0009695944,0.00268399,0.001593191,0.0004122851],"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":[0.0005633739,0.00009989127,0.001266907,0.0002251085,0.00007321735,0.0001872683,0.0005321532,0.05021491,0.001438741,0.7985445,0.007219581,0.1396344],"study_design_scores_gemma":[0.00002674873,0.00001993804,0.0002131718,0.00003520772,0.00002507133,0.0000444985,0.00005245975,0.1392238,0.00110054,0.8569871,0.002252668,0.00001877328],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01409091,0.0003031045,0.9699749,0.001107972,0.0001303147,0.00009259978,0.0002633003,0.001408512,0.01262842],"genre_scores_gemma":[0.3259028,0.0003359456,0.6643057,0.0005379549,0.0003495682,0.0003046048,0.0008382999,0.000928325,0.006496718],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01904276,"threshold_uncertainty_score":0.06370437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02474048134047621,"score_gpt":0.2384469686036217,"score_spread":0.2137064872631455,"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."}}