{"id":"W3036614154","doi":"10.1523/jneurosci.0564-20.2020","title":"Global Motion Processing by Populations of Direction-Selective Retinal Ganglion Cells","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Retinal Development and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Eye Institute","keywords":"Decoding methods; Stimulus (psychology); Neuroscience; Population; Retina; Neural coding; Neural decoding; Computer science; Sensory system; Artificial intelligence; Biology; Psychology; Algorithm","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":[0.00008425918,0.00005473853,0.00007340208,0.00001993952,0.00005834017,0.00001694237,0.0001128718,0.00002818463,0.000001543723],"category_scores_gemma":[0.0001641101,0.00004821986,0.00004426523,0.0002918727,0.00005408988,0.00001513731,0.00002136321,0.00004549879,2.778764e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009325555,"about_ca_system_score_gemma":0.00007218038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001668675,"about_ca_topic_score_gemma":8.290048e-7,"domain_scores_codex":[0.9993957,0.00002872143,0.0001980102,0.0001160709,0.0001799253,0.00008160123],"domain_scores_gemma":[0.9995104,0.000002070406,0.0002489102,0.00003244852,0.0001457945,0.000060388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007307851,0.00003207955,0.01206138,0.000007777666,0.000001059287,0.000001539973,0.0000384105,0.0003197521,0.9830748,0.00000485805,0.002899176,0.001486107],"study_design_scores_gemma":[0.0005519164,0.001379589,0.2076787,0.00003481531,0.00002358022,0.00009589255,0.0001381396,0.001436533,0.7825928,0.0001651676,0.005710886,0.0001920208],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783812,0.0001809185,0.02015097,0.0005497586,0.000219373,0.00004446435,0.000004025122,0.0000028313,0.0004665301],"genre_scores_gemma":[0.9990624,0.00005039541,0.0005551199,0.0002457794,0.00005517828,3.321454e-7,0.000001693248,0.000002905581,0.00002623901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.200482,"threshold_uncertainty_score":0.1966349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0166351567063648,"score_gpt":0.266676624310871,"score_spread":0.2500414676045062,"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."}}