{"id":"W1587153339","doi":"10.1023/a:1011187530616","title":"On the Sequential Accumulation of Evidence","year":2001,"lang":"en","type":"article","venue":"International Journal of Computer Vision","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Artificial intelligence; Cognitive neuroscience of visual object recognition; Chaining; Probabilistic logic; Pattern recognition (psychology); Robustness (evolution); Bayesian probability; Parametric statistics; Machine learning; Object (grammar); Mathematics","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":[0.02583718,0.002301245,0.005296581,0.006164889,0.001657283,0.00514854,0.00543845,0.004241132,0.00574578],"category_scores_gemma":[0.1092172,0.003521012,0.002502911,0.006017001,0.007346366,0.01523956,0.0109975,0.005104567,0.0009873379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002143468,"about_ca_system_score_gemma":0.003462448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006751676,"about_ca_topic_score_gemma":0.00625297,"domain_scores_codex":[0.988679,0.004576608,0.00119654,0.002131219,0.00278572,0.0006308971],"domain_scores_gemma":[0.848294,0.1264591,0.005875361,0.009658181,0.007884829,0.001828622],"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":[0.001197839,0.0001644239,0.004874113,0.0008092042,0.0006529073,0.0005598997,0.0008058582,0.2496531,0.002344512,0.4990344,0.005190233,0.2347134],"study_design_scores_gemma":[0.0001119799,0.0001760561,0.0007993439,0.0001504207,0.0001260425,0.000181071,0.00005813903,0.5114846,0.0009084186,0.4831664,0.0027753,0.00006223296],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01040294,0.001603204,0.9847834,0.00100458,0.0001226672,0.00009778112,0.0001566979,0.0001963261,0.001632486],"genre_scores_gemma":[0.3360282,0.003920865,0.6490718,0.0007521243,0.0007871415,0.0005368494,0.001074672,0.0002618514,0.007566441],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02583718,"threshold_uncertainty_score":0.1366417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1616690335916347,"score_gpt":0.3982887311300411,"score_spread":0.2366196975384064,"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."}}