{"id":"W2164861310","doi":"10.1162/0899766041941907","title":"A Temporal Stability Approach to Position and Attention-Shift-Invariant Recognition","year":2004,"lang":"en","type":"article","venue":"Neural Computation","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Covert; Invariant (physics); Artificial intelligence; Computer science; Artificial neural network; Saccadic masking; Pattern recognition (psychology); Eye movement; Computer vision; Speech recognition; 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":[0.0001671595,0.0001118493,0.00009602394,0.0000910307,0.0002365047,0.0001489909,0.00005321237,0.00005222901,0.00001353772],"category_scores_gemma":[0.00007931406,0.0001097248,0.0000298877,0.0002746847,0.00003555397,0.000360905,0.00002798244,0.000107672,0.00006634447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005923492,"about_ca_system_score_gemma":0.00002123849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000490696,"about_ca_topic_score_gemma":0.000006495458,"domain_scores_codex":[0.9988983,0.0001322872,0.0001914115,0.0004110376,0.0002189528,0.0001480089],"domain_scores_gemma":[0.999682,0.00003036896,0.00006745147,0.0000689787,0.00004740185,0.0001037789],"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":[0.0002126303,0.0005340965,0.0003356661,0.0001314815,0.000002705718,0.000007322627,0.003086708,0.003328093,0.9451522,0.002329872,0.00003273115,0.04484651],"study_design_scores_gemma":[0.006490534,0.00302561,0.1655702,0.0002464989,0.00008125594,0.0004930381,0.001045713,0.21907,0.3552672,0.2468741,0.00005167256,0.001784155],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8029286,0.000002016038,0.1952558,0.0008187685,0.000126519,0.0002844743,0.000009656693,0.0001354687,0.0004386408],"genre_scores_gemma":[0.9920925,0.000001123241,0.006286985,0.001463451,0.00005388299,0.00002118884,0.00006290956,0.00001165432,0.000006250067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.589885,"threshold_uncertainty_score":0.4474448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1067882705788425,"score_gpt":0.3185730706347709,"score_spread":0.2117848000559284,"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."}}