{"id":"W4232510279","doi":"10.1515/iupac.88.0266","title":"Fusion","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; National Research Council Canada","funders":"","keywords":"Computer science; Extraction (chemistry); Sample (material); Throughput; Process engineering; Chromatography; Chemistry; Engineering","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":[0.00196569,0.002719719,0.001598304,0.004776829,0.001453092,0.003177816,0.003215012,0.002272106,0.06366581],"category_scores_gemma":[0.009604842,0.0005913529,0.002735358,0.006457699,0.0004947326,0.002583076,0.003122594,0.002134264,0.1004094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00182974,"about_ca_system_score_gemma":0.003439679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0182102,"about_ca_topic_score_gemma":0.03341061,"domain_scores_codex":[0.9972559,0.0004847828,0.0003365655,0.001002281,0.0005727891,0.0003477077],"domain_scores_gemma":[0.9967476,0.0009136812,0.0003867165,0.0009751795,0.0008037827,0.0001729889],"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":[0.0004060428,0.00004507616,0.004008947,0.003570698,0.0002168064,0.00006861217,0.00006067032,0.001153675,0.0005758612,0.003193093,0.9655111,0.02118932],"study_design_scores_gemma":[0.0001371998,0.00003362383,0.004394318,0.0007094156,0.00007767411,0.00009367356,0.00007587913,0.000631089,0.0006166635,0.00361708,0.9895817,0.00003173395],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002685909,0.0003641178,0.0003903235,0.0001086051,0.00004342645,0.00002751446,0.9964458,0.0007161229,0.001635461],"genre_scores_gemma":[0.0005636286,0.0002412945,0.000762186,0.00008815323,0.000008712226,0.00007900294,0.9975401,0.0000797672,0.0006371404],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06366581,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02936210134457633,"score_gpt":0.4493720233669329,"score_spread":0.4200099220223566,"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."}}