{"id":"W1986870211","doi":"10.1167/12.11.22","title":"The Open Perimetry Interface: An enabling tool for clinical visual psychophysics","year":2012,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Australian Research Council","keywords":"Computer science; Interface (matter); Computer vision; Artificial intelligence; Psychophysics; Set (abstract data type); Human–computer interaction; Psychology; Programming language","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":[0.002766919,0.00008949407,0.0001719333,0.00004259811,0.000402212,0.0004335902,0.000583592,0.00006880404,0.00004740254],"category_scores_gemma":[0.0008657899,0.00005306347,0.0001245728,0.0001280221,0.00005497594,0.001263514,0.0001091812,0.0002907957,0.00002493078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002162077,"about_ca_system_score_gemma":0.00005171471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.234443e-7,"about_ca_topic_score_gemma":1.111395e-7,"domain_scores_codex":[0.9985967,0.0002555323,0.0005212794,0.0001330904,0.000281471,0.0002119272],"domain_scores_gemma":[0.998755,0.0004382004,0.0004050492,0.0001375402,0.0001190826,0.0001450974],"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":[0.0007346055,0.0005872782,0.0001392592,0.000008481816,0.000004266755,6.547328e-7,0.000358912,0.000005220613,0.7366414,0.0005372324,0.002595705,0.2583869],"study_design_scores_gemma":[0.007398434,0.01839254,0.0136856,0.0005306005,0.0001179451,0.0003262259,0.002529841,0.01405323,0.5686952,0.01012233,0.3632446,0.0009034901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973146,0.0001379019,0.02339451,0.000360789,0.00260189,0.0001745431,0.000001380897,0.00001095652,0.0001720586],"genre_scores_gemma":[0.9953972,0.000174993,0.002110167,0.0009203051,0.001059496,0.000001737422,2.4058e-7,0.00001706692,0.0003187901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3606489,"threshold_uncertainty_score":0.4181121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1899174468031351,"score_gpt":0.5376864759756131,"score_spread":0.347769029172478,"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."}}