{"id":"W2077959290","doi":"10.7490/f1000research.1093245.1","title":"Stereoscopy benefits processing of dynamic visual scenes by disambiguating object occlusions","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Open peer review; Plant biology; Stereoscopy; Object (grammar); Computer vision; Computer science; Neuroscience; Artificial intelligence; Communication; Computer graphics (images); Biology; Psychology","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":[0.0001118323,0.0001286705,0.0001573973,0.00008037648,0.000195326,0.0001513282,0.0004541864,0.00002729726,0.00006435246],"category_scores_gemma":[0.00004526459,0.0001028332,0.0000396248,0.0003536224,0.00004318931,0.001276688,0.0003805748,0.0000826435,0.00003882084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002235459,"about_ca_system_score_gemma":0.00004125182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007308297,"about_ca_topic_score_gemma":0.000006501359,"domain_scores_codex":[0.9988732,0.00003221604,0.0002746929,0.0003087631,0.0002459186,0.0002652603],"domain_scores_gemma":[0.9993622,0.00005924938,0.0001247607,0.0002419994,0.0001252436,0.0000865745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[5.364512e-7,0.00005279665,0.0005419409,0.0000182497,0.000002286362,2.621832e-7,0.0002778701,0.00002194479,0.0352759,0.0002787475,0.0001569697,0.9633725],"study_design_scores_gemma":[0.000220844,0.0000605282,0.003826316,0.0001464389,0.000002268021,0.000004440149,0.0002564733,0.9787048,0.01580077,0.0007256065,0.0000632911,0.0001882186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1294209,0.0003515556,0.8682241,0.0004445472,0.00008884189,0.000135988,0.000001132769,0.000153404,0.001179553],"genre_scores_gemma":[0.74247,0.00001149508,0.2569423,0.0002479824,0.000006825312,0.000006374073,0.000001909556,0.000008231569,0.0003048988],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9786829,"threshold_uncertainty_score":0.4193417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008050681525157689,"score_gpt":0.2931901310653509,"score_spread":0.2851394495401932,"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."}}