{"id":"W6930151874","doi":"10.5281/zenodo.10694607","title":"HTRA1: A Target Enabling Package","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Renal Diseases and Glomerulopathies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Serine protease; Process (computing); Quality (philosophy); Expression (computer science); Protease","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001877604,0.001612866,0.001373704,0.001304539,0.0005155437,0.002425681,0.002355608,0.001474954,0.2385083],"category_scores_gemma":[0.004875179,0.001154619,0.001348392,0.001157286,0.0003781309,0.002160709,0.002384453,0.001840005,0.2105847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005665945,"about_ca_system_score_gemma":0.0009383739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006058479,"about_ca_topic_score_gemma":0.0005124315,"domain_scores_codex":[0.9993881,0.0001013783,0.00005367704,0.0001084836,0.0002499932,0.00009829747],"domain_scores_gemma":[0.9982563,0.0006143032,0.0001283409,0.0004045359,0.0003723388,0.0002242835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002120684,0.0001686367,0.001347081,0.002254091,0.0001320881,0.0006761458,0.0002175568,0.002326245,0.03348081,0.00969351,0.7914647,0.1561184],"study_design_scores_gemma":[0.0005691553,0.0002916558,0.002531382,0.0002837231,0.0001431955,0.0008592645,0.00005690373,0.009209758,0.05121545,0.01535058,0.9193012,0.0001877808],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.003216946,0.001018333,0.2178155,0.0009459013,0.0005385421,0.0006416111,0.1144817,0.628985,0.03235647],"genre_scores_gemma":[0.06418476,0.004268314,0.1883437,0.002395779,0.00105033,0.003146918,0.3549941,0.2567766,0.1248395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2385083,"threshold_uncertainty_score":0.7978898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0281654422795745,"score_gpt":0.2663829241313502,"score_spread":0.2382174818517757,"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."}}