{"id":"W4401328231","doi":"10.1371/journal.pcbi.1011431","title":"Attentional selection and communication through coherence: Scope and limitations","year":2024,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Coherence (philosophical gambling strategy); Scope (computer science); Selection (genetic algorithm); Computer science; Cognitive psychology; Psychology; Data science; Cognitive science; Artificial intelligence; Mathematics; Statistics","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":[0.004218237,0.000508918,0.0008108203,0.0004899797,0.0006195525,0.002011473,0.002371103,0.001889757,0.002999166],"category_scores_gemma":[0.01943156,0.000517219,0.0009035561,0.0005537978,0.003016105,0.005790864,0.002479848,0.001631425,0.0002653257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006948923,"about_ca_system_score_gemma":0.000993723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002443673,"about_ca_topic_score_gemma":0.00123717,"domain_scores_codex":[0.9982809,0.0009604813,0.00009291857,0.0002382591,0.0003366743,0.00009081633],"domain_scores_gemma":[0.9869631,0.0101981,0.0004531477,0.001598211,0.0005114095,0.0002761103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001986256,0.0000730532,0.00370906,0.0006456352,0.0001741461,0.0003666239,0.0007490349,0.1336244,0.01147007,0.7808199,0.001301482,0.06686784],"study_design_scores_gemma":[0.00005945292,0.00007495382,0.002681603,0.00008596908,0.00004139643,0.0002147802,0.0002315256,0.4240249,0.001288088,0.5684173,0.002830597,0.00004949569],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3141906,0.01055893,0.59267,0.02719987,0.0004343932,0.0001444633,0.0002668258,0.0004006682,0.05413423],"genre_scores_gemma":[0.9736719,0.001618064,0.02325808,0.0002015552,0.0001447607,0.0001296369,0.00003684668,0.00005838173,0.0008807681],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004218237,"threshold_uncertainty_score":0.02230841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08422949403857763,"score_gpt":0.3054213115462266,"score_spread":0.221191817507649,"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."}}