{"id":"W6931653780","doi":"10.5281/zenodo.7888903","title":"Rosa xanthina Lindl.","year":2014,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Nuclear Structure and Function","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"","keywords":"Yield (engineering); Selection (genetic algorithm); Quality (philosophy)","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":[0.0001321663,0.000536098,0.0003064385,0.0007087742,0.0005286575,0.0003025497,0.0003785646,0.0002377189,0.00811576],"category_scores_gemma":[0.00006853408,0.0002375166,0.0002624614,0.0003317264,0.000111502,0.0004426953,0.0004708897,0.0006438838,0.007123027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005270243,"about_ca_system_score_gemma":0.0001431658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00210492,"about_ca_topic_score_gemma":0.003200067,"domain_scores_codex":[0.9999096,0.000008818789,0.00000611873,0.0000433666,0.00002384693,0.000008297572],"domain_scores_gemma":[0.9999272,0.000008780233,0.00002289378,0.000009196813,0.00001251571,0.00001950056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002050584,0.00009588583,0.001191407,0.0002707295,0.00002055329,0.0003241407,0.0001042465,0.0001134719,0.9656354,0.001342931,0.003099396,0.02759687],"study_design_scores_gemma":[0.0001949419,0.0009238737,0.1039042,0.0002180068,0.0001636938,0.002790871,0.0004027765,0.001237376,0.2462662,0.002344543,0.6414613,0.00009225604],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7004777,0.02632647,0.03057339,0.003115969,0.0007658349,0.0006651094,0.04011415,0.006038277,0.1919232],"genre_scores_gemma":[0.6800911,0.004606306,0.02508274,0.001700234,0.0001158342,0.0003741539,0.04026845,0.0006228228,0.2471384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00811576,"threshold_uncertainty_score":0.02714998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01239345461473478,"score_gpt":0.2171640787861277,"score_spread":0.2047706241713929,"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."}}