{"id":"W1973190487","doi":"10.1007/s00221-005-0164-1","title":"Transsaccadic integration of visual features in a line intersection task","year":2005,"lang":"en","type":"article","venue":"Experimental Brain Research","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Intersection (aeronautics); Task (project management); Neuroscience; Line (geometry); Computer science; Artificial intelligence; Communication; Psychology; Computer vision; Engineering; Mathematics; Geometry; Transport engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009517423,0.0007732456,0.0007915236,0.0003896796,0.0003554137,0.001151335,0.0008055564,0.000926704,0.00561765],"category_scores_gemma":[0.006398947,0.0004434053,0.0002009982,0.0004499496,0.0004601969,0.001839542,0.001504221,0.001266636,0.0006865148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002877846,"about_ca_system_score_gemma":0.0006073439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009918432,"about_ca_topic_score_gemma":0.0009444679,"domain_scores_codex":[0.999409,0.00008989024,0.00005169036,0.0001274485,0.0002400104,0.00008193572],"domain_scores_gemma":[0.998549,0.0006987281,0.0002203998,0.0001898927,0.0001136936,0.0002281722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01139724,0.001195671,0.003536241,0.0002341997,0.00008034823,0.0002074366,0.000454265,0.001856755,0.9173397,0.004275118,0.0008137253,0.05860922],"study_design_scores_gemma":[0.004306718,0.01684037,0.3327851,0.0002042081,0.0008485398,0.0029906,0.001174055,0.2159045,0.3805896,0.03606991,0.007980353,0.0003060541],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9834874,0.00008547938,0.01002843,0.00009459393,0.00006409428,0.00007461554,0.0001168669,0.0001509822,0.005897441],"genre_scores_gemma":[0.9873362,0.0001064776,0.01022836,0.0001151845,0.00002988541,0.0001062767,0.000214117,0.0001290128,0.001734559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00561765,"threshold_uncertainty_score":0.01879293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.121757785422812,"score_gpt":0.4770969792761878,"score_spread":0.3553391938533759,"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."}}