{"id":"W2163784478","doi":"10.1109/pacrim.2007.4313262","title":"Difference Closeness Function for Eye Array","year":2007,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Closeness; Computer science; Analogy; Function (biology); Lens (geology); Pinhole (optics); Artificial intelligence; Computer vision; Theoretical computer science; Algorithm; Mathematics; Optics; Physics; Mathematical analysis","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":[0.0002224913,0.0000625442,0.00006157647,0.00004375145,0.0001048686,0.0001010117,0.0002604088,0.00003172805,0.000008239306],"category_scores_gemma":[0.00002118412,0.0000491707,0.00003024054,0.0001639528,0.00001168284,0.0002235119,0.00002623221,0.00003538053,0.00001958561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001322553,"about_ca_system_score_gemma":0.00002364915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002952571,"about_ca_topic_score_gemma":0.000010956,"domain_scores_codex":[0.9993749,0.000003932673,0.00009946942,0.0001996612,0.0001060475,0.000216018],"domain_scores_gemma":[0.9996248,0.00005711521,0.00003327411,0.0001729137,0.00005868634,0.00005315106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001740206,0.00003484613,0.003034029,0.00001889125,0.000005383697,0.000001320459,0.0000971176,0.000002654968,0.2049154,0.01280582,0.0003065267,0.7787606],"study_design_scores_gemma":[0.0002443632,0.00007427463,0.02467316,0.00001035967,0.00000270605,0.000002191999,0.00002581784,0.0005047754,0.950471,0.01757042,0.006283156,0.0001377366],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04296067,0.00003868901,0.9494218,0.0003254774,0.0004163905,0.00006833031,1.699136e-7,0.0001629903,0.006605497],"genre_scores_gemma":[0.8138719,0.000001030608,0.182975,0.0006809512,0.0001324812,0.000004964939,8.036197e-7,0.000003615828,0.002329337],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7786229,"threshold_uncertainty_score":0.2005123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0172435921411949,"score_gpt":0.2678639935963011,"score_spread":0.2506204014551062,"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."}}