{"id":"W6906670875","doi":"10.18419/darus-2727/5","title":"lNMR.zip","year":2023,"lang":"fr","type":"dataset","venue":"Universitätsbibliothek Stuttgart","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; European Commission","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001126969,0.004124628,0.002489571,0.004802702,0.001325548,0.00413722,0.00370888,0.003628372,0.2270448],"category_scores_gemma":[0.007499336,0.001095932,0.001321602,0.007626448,0.0006343742,0.003064263,0.002858071,0.002252222,0.4540822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00183845,"about_ca_system_score_gemma":0.001896286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01470196,"about_ca_topic_score_gemma":0.0251505,"domain_scores_codex":[0.9985662,0.0002770534,0.0001166075,0.0005303382,0.0002771745,0.0002326341],"domain_scores_gemma":[0.9976107,0.000650121,0.0001697245,0.0007625278,0.000521827,0.0002850804],"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":[0.00004551706,0.00001658268,0.0001217736,0.0003362013,0.000009722004,0.000007561712,0.000008224913,0.0001098994,0.00005983282,0.0002803657,0.9973341,0.00167025],"study_design_scores_gemma":[0.0002413511,0.00002813108,0.0008691777,0.0001888427,0.00001852681,0.0000453018,0.00004953145,0.0005546773,0.0002887355,0.001454341,0.9962365,0.00002494258],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009013462,0.000125279,0.00007960644,0.0001080797,0.00004558575,0.0000127768,0.9963788,0.001354071,0.00180575],"genre_scores_gemma":[0.0002706996,0.00007889078,0.0002437481,0.0000768415,0.00001375294,0.00004788241,0.9978411,0.000183826,0.001243298],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7729552,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02598523713391175,"score_gpt":0.2657130687461648,"score_spread":0.2397278316122531,"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."}}