{"id":"W2168815516","doi":"10.1016/s0042-6989(01)00247-4","title":"Rules for combining the outputs of local motion detectors to define simple contours","year":2002,"lang":"en","type":"article","venue":"Vision Research","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Motion (physics); Computer vision; Artificial intelligence; Structure from motion; Motion field; Computer science; Simple (philosophy); Fidelity; Field (mathematics); Physics; Motion detection; Space (punctuation); Optics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001218125,0.00007501931,0.0001119557,0.0001901069,0.0004482765,0.00008285982,0.0003207017,0.00005629372,0.0003293381],"category_scores_gemma":[0.001278227,0.00005119145,0.00004849828,0.0004657258,0.0001616497,0.00007771301,0.0001101111,0.0001842858,0.0002502039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003028522,"about_ca_system_score_gemma":0.0000147585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000027825,"about_ca_topic_score_gemma":0.00001158879,"domain_scores_codex":[0.9982764,0.000280241,0.0001891383,0.0002732204,0.0006552054,0.0003258017],"domain_scores_gemma":[0.99868,0.00076759,0.00003867282,0.0002180711,0.0001884096,0.0001072385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007812693,0.0001179577,0.00002006653,0.00003482337,0.000001070794,0.000001110344,0.0007555872,0.00008741979,0.7771255,0.00519814,0.004968666,0.2116115],"study_design_scores_gemma":[0.0008353762,0.001791412,0.0008618272,0.00007326153,0.000003421916,0.000004360314,0.001164723,0.05497515,0.9208411,0.006621129,0.01267915,0.0001490641],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9039658,0.00003532618,0.09198371,0.002282198,0.0001335298,0.0005800437,0.00002146278,0.0000521288,0.0009458568],"genre_scores_gemma":[0.9986882,0.00001359626,0.0002578686,0.0003640397,0.00003458024,0.00003560198,0.000001564234,0.000014866,0.0005897169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2114625,"threshold_uncertainty_score":0.3606021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.264090647648656,"score_gpt":0.4516503111157844,"score_spread":0.1875596634671283,"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."}}