{"id":"W2035911806","doi":"10.1167/5.8.481","title":"Spatiotemporal templates for detecting 1st- and 2nd-order orientation- and luminance-defined targets","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Infrared Target Detection Methodologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Luminance; Artificial intelligence; Computer science; Computer vision; Orientation (vector space); Stimulus (psychology); Frame (networking); Pattern recognition (psychology); Template; Mathematics; Psychology","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":[0.0006862996,0.0001578593,0.0001989294,0.0002853138,0.0000944022,0.0003328292,0.0002087385,0.0002605131,0.000764881],"category_scores_gemma":[0.004005318,0.0002455005,0.00024245,0.0002138823,0.0001619419,0.0004629644,0.0002023902,0.0002427456,0.0002322274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002069611,"about_ca_system_score_gemma":0.0002251665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001400378,"about_ca_topic_score_gemma":0.001825846,"domain_scores_codex":[0.999719,0.00005644141,0.00002538836,0.0000867397,0.00008069044,0.00003171725],"domain_scores_gemma":[0.9982553,0.00073607,0.0003462645,0.0003072576,0.0002556142,0.00009940712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000381016,0.0000186972,0.003323426,0.0000755448,0.00001159643,0.00005808079,0.000155309,0.001004705,0.963534,0.0003194035,0.000112536,0.03100574],"study_design_scores_gemma":[0.00006093232,0.0007953832,0.1780166,0.0000271725,0.00007460857,0.001443553,0.0001127856,0.1022545,0.7148101,0.0007782396,0.001551959,0.00007403023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.835305,0.0002863624,0.1627917,0.00003780193,0.00002402615,0.00006508432,0.00017729,0.0002335688,0.001079146],"genre_scores_gemma":[0.9199027,0.0001440233,0.07920896,0.00001379957,0.000009939969,0.00004021878,0.0002033351,0.00005046735,0.0004264585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001400378,"threshold_uncertainty_score":0.003629565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01721992382277902,"score_gpt":0.2932392925767085,"score_spread":0.2760193687539295,"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."}}