{"id":"W4233989059","doi":"10.1515/iupac.85.0431","title":"Einzel Lens","year":2016,"lang":"de","type":"dataset","venue":"IUPAC Standards Online","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; National Research Council Canada","funders":"","keywords":"Terminology; Chemical nomenclature; Mass spectrometry; Standardization; Chemistry; Accelerator mass spectrometry; Analytical Chemistry (journal); Political science; Environmental chemistry; Chromatography; Law; Linguistics","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":[0.001640172,0.001730748,0.001677235,0.005498312,0.001165176,0.00746159,0.001907428,0.001466524,0.5219613],"category_scores_gemma":[0.01740672,0.00064097,0.001716222,0.01115802,0.0004302291,0.005062921,0.003582877,0.001849146,0.5473443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002252632,"about_ca_system_score_gemma":0.003938616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0100325,"about_ca_topic_score_gemma":0.01282386,"domain_scores_codex":[0.9966385,0.0005615142,0.0005440625,0.0009501554,0.0009439452,0.0003618054],"domain_scores_gemma":[0.9930581,0.002000217,0.0007484783,0.001691894,0.002063285,0.0004380495],"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":[0.00005543968,0.000006744242,0.0004515277,0.0007793221,0.0000192582,0.00001568125,0.00002663805,0.0000541407,0.0000508812,0.001479525,0.980371,0.01668969],"study_design_scores_gemma":[0.00002220159,0.000004109902,0.0008198326,0.0003274503,0.000009439382,0.00002804235,0.00005222279,0.00003318201,0.00007758063,0.001147457,0.9974699,0.000008574548],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001504649,0.0006335289,0.000345901,0.0004936273,0.0002358402,0.00004273943,0.9783062,0.0013321,0.01845951],"genre_scores_gemma":[0.001148881,0.001376366,0.001209461,0.0006319581,0.0001255634,0.0002161318,0.9718165,0.001064775,0.02241044],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5219613,"threshold_uncertainty_score":0.6818642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01513793067223277,"score_gpt":0.3862132957539651,"score_spread":0.3710753650817323,"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."}}