{"id":"W4400033206","doi":"10.1101/2024.06.24.600439","title":"Visual search efficiency is modulated by symmetry type and texture regularity","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Texture (cosmology); Type (biology); Symmetry (geometry); Computer vision; Artificial intelligence; Computer science; Mathematics; Image (mathematics); Geometry; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005167816,0.0002039661,0.0005172545,0.0005743442,0.000129282,0.0009746733,0.0002895421,0.0003858037,0.002221207],"category_scores_gemma":[0.007059158,0.0002890101,0.0002259735,0.0003943451,0.000362842,0.0006019019,0.0004867309,0.0003223729,0.0002540953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002203404,"about_ca_system_score_gemma":0.0001051458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005784585,"about_ca_topic_score_gemma":0.0004232972,"domain_scores_codex":[0.9996147,0.00007513747,0.00003815779,0.0001079812,0.000109713,0.00005420524],"domain_scores_gemma":[0.9949028,0.002464516,0.001558746,0.0005126644,0.0002633464,0.0002978752],"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":[0.002761466,0.0002842699,0.04677816,0.0001899779,0.0001585768,0.0001055427,0.0002224864,0.00302109,0.9312495,0.0006221306,0.0003254672,0.01428144],"study_design_scores_gemma":[0.0002098444,0.001069103,0.8782074,0.00002833094,0.0001060071,0.000422507,0.0002102306,0.04049331,0.0761755,0.002506638,0.0005092739,0.0000618508],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982191,0.00007785778,0.001054017,0.00001548832,0.000002471654,0.000007536112,0.00006158212,0.00002168374,0.0005402502],"genre_scores_gemma":[0.998835,0.0000238743,0.0008412252,0.000009461184,0.000002527877,0.000007925533,0.00008170434,0.00002279931,0.0001754932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002221207,"threshold_uncertainty_score":0.007430673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01212410832302857,"score_gpt":0.2496066166604023,"score_spread":0.2374825083373737,"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."}}