{"id":"W178275036","doi":"","title":"SOUNDVIEW: SENSING COLOR IMAGES BY KINESTHETIC AUDIO","year":2003,"lang":"en","type":"article","venue":"","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; Color space; Color image; Computer graphics (images); Image (mathematics); Image processing","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00002599438,0.00009669257,0.00009678116,0.00004015969,0.0001777725,0.00007893278,0.0000628778,0.00003072021,0.0006720742],"category_scores_gemma":[0.0004228078,0.00008118227,0.00005251065,0.0001444492,0.00006085741,0.0001699177,0.00000878242,0.0001102139,0.0009496675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002421223,"about_ca_system_score_gemma":0.00001671394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000203893,"about_ca_topic_score_gemma":0.000007393309,"domain_scores_codex":[0.9992008,0.0001006941,0.0001283649,0.0002452908,0.0001186382,0.0002062348],"domain_scores_gemma":[0.9994763,0.0002132387,0.00004003698,0.0001849641,0.00002386116,0.00006161377],"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":[0.000003595201,0.00004133657,0.00002388592,0.0000020636,0.000001261368,0.0000225928,0.00005200655,0.00000912744,0.9642577,0.001761425,0.03320173,0.00062323],"study_design_scores_gemma":[0.00008462399,0.00002046356,0.00001539384,0.000002844177,0.000004448669,0.000255928,0.0000715657,0.00009176356,0.6517779,0.0001832487,0.3474069,0.00008487998],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7255669,0.00002014288,0.001856616,0.001389725,0.0006631122,0.0001693143,0.000008691697,0.0002263593,0.2700992],"genre_scores_gemma":[0.9579084,0.00002718443,0.0003451175,0.002559286,0.0000184451,0.000001867442,5.184243e-7,0.00001288198,0.03912628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3142052,"threshold_uncertainty_score":0.9998282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0259079870629206,"score_gpt":0.2751781695530391,"score_spread":0.2492701824901185,"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."}}