{"id":"W4393878763","doi":"10.5281/zenodo.4115639","title":"20201020_NSD2_208-368_NHis _Purification Protocol","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Protocol (science); Chemistry; Computer science; Medicine","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":[0.00177105,0.003157594,0.001561948,0.002989175,0.001099301,0.00227355,0.003624839,0.002518034,0.1185512],"category_scores_gemma":[0.006514683,0.001067207,0.002030088,0.00402667,0.0005725555,0.001551192,0.001838549,0.002207431,0.1536079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001572921,"about_ca_system_score_gemma":0.003453128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02671252,"about_ca_topic_score_gemma":0.039254,"domain_scores_codex":[0.9985487,0.000303263,0.0001523956,0.0004781423,0.0003019681,0.0002155068],"domain_scores_gemma":[0.9978442,0.0006164732,0.0001381738,0.0006147023,0.0005235526,0.0002628347],"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":[0.00009395921,0.00002592295,0.0004587078,0.0004942049,0.00003015572,0.00001200904,0.00001313141,0.0004913465,0.000326232,0.0003338796,0.9959931,0.001727262],"study_design_scores_gemma":[0.0005249311,0.00004005119,0.002437063,0.0002045418,0.00007006941,0.00005792451,0.00005738085,0.001358921,0.001385751,0.002609231,0.9911972,0.0000569348],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001077123,0.0000446886,0.000172684,0.00004806263,0.00002828119,0.0000233446,0.9982153,0.0007910404,0.0005689373],"genre_scores_gemma":[0.0001724781,0.00003081384,0.0004451182,0.00005187343,0.000003531122,0.0001012056,0.998623,0.0001418814,0.0004300663],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1185512,"threshold_uncertainty_score":0.3965934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05778382819765072,"score_gpt":0.2810121486779567,"score_spread":0.223228320480306,"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."}}