{"id":"W1994479093","doi":"10.1142/s0219878904000033","title":"VISUAL INFORMATION ACQUISITION IN VERTEBRATE RETINA","year":2004,"lang":"en","type":"article","venue":"International Journal of Information Acquisition","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Retina; Neurophysiology; Vertebrate; Artificial neural network; Neuroscience; Retinal; Artificial intelligence; Computer vision; Biology","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":[0.0003242732,0.0001315448,0.0001411895,0.0008476088,0.00003064015,0.0002163142,0.0002085327,0.00008257442,0.0001746127],"category_scores_gemma":[0.00004868228,0.0001348636,0.0000852986,0.00023251,0.00002272162,0.007735388,0.00001978154,0.000215963,0.0002584324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005561882,"about_ca_system_score_gemma":0.00005438174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009480309,"about_ca_topic_score_gemma":0.000001603408,"domain_scores_codex":[0.9983034,0.00001777791,0.0009139972,0.00003805725,0.0005760631,0.0001507521],"domain_scores_gemma":[0.9989684,0.00001861324,0.0003228761,0.00006575904,0.0005629156,0.00006148378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006222856,0.0001736128,0.002875419,0.0001371196,0.0002181659,0.00006675972,0.008373365,0.8433136,0.004649815,0.01013749,0.004666059,0.1247662],"study_design_scores_gemma":[0.04061866,0.001401931,0.1823785,0.00414701,0.0001592333,0.004804682,0.01093458,0.5184699,0.1291129,0.03205644,0.07282662,0.003089565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9115753,0.00005511956,0.07653331,0.001156852,0.00264327,0.0001529392,0.0000276864,0.0001352551,0.007720292],"genre_scores_gemma":[0.9975188,0.00009665059,0.001156676,0.0008635839,0.0001948999,0.000003366379,0.0001551089,0.000007629258,0.000003275456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3248438,"threshold_uncertainty_score":0.560797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002652047561952133,"score_gpt":0.2198734544491426,"score_spread":0.2172214068871905,"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."}}