{"id":"W2140616900","doi":"","title":"Perceiving filled vs. empty time intervals: A comparison of adjustment and magnitude estimation methods","year":2012,"lang":"en","type":"article","venue":"Proceedings of Fechner Day","topic":"Neuroscience and Music Perception","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Illusion; Duration (music); Time perception; Statistics; Interval (graph theory); Magnitude (astronomy); Perception; Mathematics; Offset (computer science); Estimation; Psychophysics; Audiology; Psychology; Cognitive psychology; Computer science; Acoustics; Medicine; Physics; Engineering","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":[0.0009090106,0.000141535,0.0003012725,0.0001646905,0.00008210451,0.00003126973,0.0002120562,0.00006179937,0.0000798016],"category_scores_gemma":[0.001036862,0.0001213804,0.00005393388,0.0002747746,0.0001968108,0.0008212177,0.0001781804,0.0001285019,0.00001187169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002894132,"about_ca_system_score_gemma":0.00001017327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008113298,"about_ca_topic_score_gemma":1.875898e-7,"domain_scores_codex":[0.9987668,0.00003859033,0.000356745,0.0002837436,0.0002931647,0.0002609498],"domain_scores_gemma":[0.9993144,0.0001446471,0.0002807864,0.00008785122,0.00008101499,0.00009129583],"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":[0.00001798289,0.000164743,0.001610569,0.0001026717,0.000001661679,5.263335e-8,0.005593861,0.000001875758,0.9525775,0.0002081207,0.000519686,0.03920127],"study_design_scores_gemma":[0.0002805059,0.0002450242,0.09405316,0.0001350112,0.00004491787,0.00001811181,0.0004107221,0.0102528,0.8938515,0.0001688643,0.0003737597,0.000165662],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962692,0.00003906832,0.001146403,0.00009910183,0.0001643032,0.0002755221,0.000004064676,0.00005954682,0.001942761],"genre_scores_gemma":[0.9791372,0.00002883626,0.02041546,0.0001573739,0.00004215809,0.00002250546,7.37909e-7,0.00001243315,0.0001832938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09244259,"threshold_uncertainty_score":0.494975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05645088913963954,"score_gpt":0.3744339730678627,"score_spread":0.3179830839282232,"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."}}