{"id":"W2105144861","doi":"10.1002/cjs.5550340208","title":"A bayesian signal detection procedure for scale‐space random fields","year":2006,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bayesian probability; Scale space; Scale (ratio); SIGNAL (programming language); Detection theory; Computer science; Artificial intelligence; Bayes' theorem; Point (geometry); Pattern recognition (psychology); Space (punctuation); Random field; Mathematics; Image (mathematics); Image processing; Statistics; Physics; Detector","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009321538,0.0009127407,0.001491473,0.003026648,0.0008078981,0.001597355,0.002293857,0.002063876,0.004321539],"category_scores_gemma":[0.02987426,0.001066714,0.001460507,0.001562734,0.00209477,0.001835502,0.002741708,0.002086693,0.001506846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001075937,"about_ca_system_score_gemma":0.002155065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002745719,"about_ca_topic_score_gemma":0.002190306,"domain_scores_codex":[0.9949152,0.002639853,0.0002164515,0.0007537469,0.001286226,0.0001884416],"domain_scores_gemma":[0.9873347,0.009281424,0.0008005709,0.0005777382,0.001741857,0.000263654],"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":[0.0005569711,0.000195381,0.001661965,0.0003780545,0.0003173604,0.0003213774,0.000325918,0.2272633,0.02035555,0.3640879,0.004944428,0.3795916],"study_design_scores_gemma":[0.00005955428,0.00006142582,0.0004498702,0.00004028591,0.00003108426,0.0001265474,0.00001437771,0.8812271,0.003603077,0.1118091,0.002520622,0.00005702215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001225243,0.00005737739,0.9983014,0.00005978419,0.00001083769,0.00002384145,0.00001945805,0.0001094479,0.0001924654],"genre_scores_gemma":[0.06440673,0.0001851131,0.9327909,0.0001293667,0.00007350943,0.0002979566,0.0001978322,0.0001568624,0.001761775],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009321538,"threshold_uncertainty_score":0.04929763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03060087799068267,"score_gpt":0.2871092866151476,"score_spread":0.2565084086244649,"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."}}