{"id":"W1985441534","doi":"10.1097/opx.0b013e318205a162","title":"A Compact Clinical Instrument for Quantifying Suppression","year":2010,"lang":"en","type":"article","venue":"Optometry and Vision Science","topic":"Ophthalmology and Visual Impairment Studies","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science","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":[0.001784238,0.0000852156,0.0002145765,0.0001820712,0.000503364,0.00004141132,0.00009813965,0.00007584163,0.00004988263],"category_scores_gemma":[0.0006244915,0.0000565282,0.00005391498,0.0003939816,0.0008269986,0.0002192713,0.0001024347,0.0002210936,0.00001005822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006486307,"about_ca_system_score_gemma":0.00004594245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001610883,"about_ca_topic_score_gemma":1.053021e-7,"domain_scores_codex":[0.9989791,0.00001760738,0.0002181242,0.0003254811,0.0002296325,0.0002300538],"domain_scores_gemma":[0.9991735,0.0002886264,0.00006159698,0.0001784073,0.00009714241,0.0002007213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002552033,0.0003385953,0.9313329,0.00005363717,0.000007629835,0.000002171931,0.00005441107,5.259639e-8,0.05825769,0.0002513375,0.0003760209,0.009070279],"study_design_scores_gemma":[0.001245033,0.002079055,0.9867833,0.00008664909,0.0000189138,0.00006921843,0.0001385264,0.00121706,0.006381329,0.00004445036,0.001859726,0.00007674502],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970116,0.00003624752,0.0002172402,0.0009919266,0.0009007283,0.0002397859,0.000002845431,0.0000219152,0.0005777224],"genre_scores_gemma":[0.9960241,0.00002884936,0.003463681,0.0002417078,0.0000876709,0.000003518358,0.00000166726,0.000003770688,0.0001450764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05545032,"threshold_uncertainty_score":0.387152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1368879225232004,"score_gpt":0.5948594678719744,"score_spread":0.457971545348774,"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."}}