{"id":"W6930538573","doi":"10.5281/zenodo.13769507","title":"Vanhornia quizhouensis","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Holotype; Dorsum; Transverse plane; Sulcus; Margin (machine learning)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000656716,0.0003031612,0.0001723772,0.0006442678,0.000630567,0.000270827,0.0002739525,0.0001799518,0.003366464],"category_scores_gemma":[0.0001976999,0.0001192945,0.0001132879,0.0004180159,0.0002471336,0.0003891004,0.0003795065,0.0001704005,0.0005108538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003551532,"about_ca_system_score_gemma":0.0002045322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01162906,"about_ca_topic_score_gemma":0.02642029,"domain_scores_codex":[0.9999385,0.000006496804,0.000005215776,0.00002349264,0.00001216763,0.00001414149],"domain_scores_gemma":[0.9999498,0.000012375,0.00001397457,0.000005887441,0.0000127604,0.000005240026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006066515,0.0001368606,0.1202611,0.001695231,0.0001442951,0.005468756,0.003795814,0.002537288,0.2103857,0.01393139,0.01456852,0.6264684],"study_design_scores_gemma":[0.0001109916,0.0003250686,0.7421924,0.0003803605,0.000174265,0.008664906,0.001512768,0.001726087,0.01412367,0.004393421,0.2263496,0.0000465242],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8724571,0.00859875,0.003920654,0.0003169246,0.0001507593,0.0001276044,0.001516199,0.0003044272,0.1126075],"genre_scores_gemma":[0.9878385,0.0006108293,0.0009120124,0.0001179512,0.00001929001,0.00002458755,0.0005996618,0.000006735646,0.009870416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01162906,"threshold_uncertainty_score":0.02312279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02494315954391018,"score_gpt":0.2681883234511447,"score_spread":0.2432451639072346,"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."}}