{"id":"W4244466928","doi":"10.1515/iupac.85.0747","title":"Static Field","year":2016,"lang":"en","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":"Chemical nomenclature; Terminology; Mass spectrometry; Chemistry; Standardization; Accelerator mass spectrometry; Analytical Chemistry (journal); Political science; Environmental chemistry; Chromatography; Law; Organic chemistry; 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":[],"consensus_categories":[],"category_scores_codex":[0.001776547,0.002209785,0.001677256,0.006049747,0.001386315,0.004150891,0.002993663,0.001916314,0.1558615],"category_scores_gemma":[0.01442018,0.000778192,0.001679508,0.01012996,0.0005345866,0.004474769,0.002837432,0.002235942,0.2579192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002199302,"about_ca_system_score_gemma":0.004753952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02109557,"about_ca_topic_score_gemma":0.03357419,"domain_scores_codex":[0.9973069,0.0003987162,0.0004040221,0.000782654,0.0007790576,0.0003286839],"domain_scores_gemma":[0.9938949,0.001527905,0.0005968625,0.001634356,0.001973398,0.0003724918],"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":[0.00005207582,0.00001149369,0.0005381458,0.0006043154,0.00001638745,0.00001278717,0.00001910389,0.000104651,0.00006395638,0.0008590922,0.993436,0.004282101],"study_design_scores_gemma":[0.0000462639,0.00000601188,0.001088757,0.0003011226,0.00001102237,0.0000281804,0.00005535575,0.00008568819,0.0001515102,0.001300336,0.9969104,0.00001535222],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005228393,0.00008507021,0.0001049708,0.00008575901,0.00003654642,0.00001291297,0.9975221,0.0005647095,0.0015357],"genre_scores_gemma":[0.0002053473,0.0001309307,0.0003519843,0.00009978264,0.00001114622,0.00006522373,0.9977477,0.0001543087,0.001233643],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1558615,"threshold_uncertainty_score":0.5214086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118015761347364,"score_gpt":0.3966088629819678,"score_spread":0.3854287053684942,"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."}}