{"id":"W1021950454","doi":"","title":"Identification of Protein Targets of Novel Neuroprotective Sulfhydryl Reducing Drugs","year":2009,"lang":"en","type":"article","venue":"Investigative Ophthalmology & Visual Science","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Neuroprotection; Identification (biology); Chemistry; Pharmacology; Computational biology; Biology; Botany","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":[0.002477105,0.0002087062,0.0003378727,0.0004560341,0.000220303,0.00006007429,0.001627144,0.00007008903,0.000004880785],"category_scores_gemma":[0.001982061,0.0002050539,0.00007949385,0.002876987,0.002669107,0.001317236,0.0003737037,0.0002292428,0.000005117352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001061823,"about_ca_system_score_gemma":0.0007554874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007088946,"about_ca_topic_score_gemma":1.342057e-7,"domain_scores_codex":[0.9967993,0.0003664382,0.0007137093,0.0008800776,0.0008477316,0.000392738],"domain_scores_gemma":[0.9974483,0.0002828688,0.0008074903,0.0005069386,0.0007890238,0.0001654393],"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":[0.00001217887,0.0002352768,0.00009968522,0.00001223666,0.000006333051,0.000007139603,0.002087725,0.006003876,0.9705742,0.01912583,0.000001098252,0.001834441],"study_design_scores_gemma":[0.0001925207,0.0004751039,0.0466553,0.00004953706,0.000003779365,0.00004424571,0.00005823662,0.09157999,0.8070384,0.05374934,8.041468e-7,0.0001527336],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9611523,0.00003654356,0.0369187,0.0006169516,0.0001977492,0.0005495591,0.000006178513,0.00004131926,0.0004807408],"genre_scores_gemma":[0.9358599,3.536018e-7,0.06399788,0.00005689778,0.00002273164,0.0000234473,0.000001080825,0.000006275309,0.00003149295],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1635358,"threshold_uncertainty_score":0.9834436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03891387388262986,"score_gpt":0.3535533929403882,"score_spread":0.3146395190577583,"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."}}