{"id":"W4408932328","doi":"10.17504/protocols.io.n2bvj311wlk5/v1","title":"Salmaso Lab TRAP Adaptation v1","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Biological Research and Disease Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Trap (plumbing); Adaptation (eye); Computer science; Physics; Optics; Meteorology","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":[0.0001246012,0.0001904645,0.000150177,0.00003447037,0.00004371486,0.00005311466,0.0001869566,0.00033068,0.0001359653],"category_scores_gemma":[0.0002014719,0.0001345126,0.0001915495,0.00004483131,0.00009971776,4.042146e-7,0.001419383,0.0002904502,0.0001612565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001216205,"about_ca_system_score_gemma":0.000191364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004747305,"about_ca_topic_score_gemma":0.00009433564,"domain_scores_codex":[0.9988731,0.00005264063,0.0001456242,0.0005302128,0.0001497115,0.00024874],"domain_scores_gemma":[0.9994573,0.00001274452,0.00002610068,0.0002835784,0.00008992867,0.0001303644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001113088,0.0005250789,0.0008454509,0.001855098,0.002209406,0.0001189496,0.0002244078,0.0004717376,0.2271088,0.01506921,0.5584125,0.1920462],"study_design_scores_gemma":[0.00142983,0.002061058,0.009531928,0.0003601404,0.00035034,0.00001259604,0.001322543,0.002499426,0.09912591,0.1444032,0.7362964,0.00260656],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6179879,0.09419658,0.004667455,0.004797465,0.001522884,0.001363031,0.0008438681,0.0002817143,0.2743391],"genre_scores_gemma":[0.987304,0.002998278,0.0006174202,0.0003372066,0.0004867665,0.0001041738,0.0006477329,0.00001735144,0.007487079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.369316,"threshold_uncertainty_score":0.5485265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03976281547242912,"score_gpt":0.3243359600247747,"score_spread":0.2845731445523456,"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."}}