{"id":"W824117140","doi":"10.1167/15.5.1","title":"Modeling probability and additive summation for detection across multiple mechanisms under the assumptions of signal detection theory","year":2015,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research","keywords":"Psychometric function; Summation; Weibull distribution; Monte Carlo method; Function (biology); Detection theory; SIGNAL (programming language); Mathematics; Computer science; Psychophysics; Statistical physics; Statistics; Physics; Perception","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002128979,0.00008868476,0.0001349935,0.00007060183,0.0003102466,0.00006851481,0.00009405156,0.0000832245,0.000008602495],"category_scores_gemma":[0.0007832852,0.00005900511,0.0000794945,0.0001360712,0.00006405374,0.0004819198,0.00002938932,0.0001715539,0.000001574538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007422364,"about_ca_system_score_gemma":0.00004248823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004703345,"about_ca_topic_score_gemma":0.00002843715,"domain_scores_codex":[0.9987463,0.0002924324,0.0003695826,0.0001453736,0.0003276025,0.000118665],"domain_scores_gemma":[0.9987624,0.0003338071,0.0003337566,0.0000808695,0.0004185576,0.00007059469],"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":[0.0005231449,0.00006882531,0.000001223082,0.0000175728,0.000003530168,1.486843e-7,0.0009429545,0.01094628,0.9364592,0.0007293689,0.000002408683,0.05030528],"study_design_scores_gemma":[0.0007011459,0.0008179317,0.0001424727,0.00004709016,0.00001891054,0.00003641541,0.001942773,0.3882006,0.4843865,0.1236305,0.00001562317,0.00005995613],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4755925,0.00001010959,0.5240321,0.0000481257,0.000158833,0.0001379396,0.000007718865,0.00000847629,0.000004204358],"genre_scores_gemma":[0.9978288,0.00001421612,0.001970749,0.00007413991,0.00007593618,0.000008489751,7.897268e-7,0.00001011753,0.00001676897],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5222363,"threshold_uncertainty_score":0.2406159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1088646181869008,"score_gpt":0.3689203382132337,"score_spread":0.260055720026333,"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."}}