{"id":"W4250576736","doi":"10.1515/iupac.85.0780","title":"Transport Region","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001331027,0.0004005014,0.0004891096,0.0001328434,0.0001008358,0.00002211595,0.0005971578,0.0005488495,0.04685827],"category_scores_gemma":[0.00005179575,0.0003182446,0.0002349234,0.0001733946,0.0001047544,0.00004448544,0.00005979332,0.0005305123,0.000002102807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000387564,"about_ca_system_score_gemma":0.0002963817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009492867,"about_ca_topic_score_gemma":0.0001616497,"domain_scores_codex":[0.9979243,0.000008762511,0.0004449318,0.0005633975,0.0006841052,0.0003745259],"domain_scores_gemma":[0.9980071,0.00003871378,0.000261873,0.001336358,0.0002007003,0.0001552262],"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":[0.00003776831,0.0001700808,0.00001462636,0.0002178228,0.00004658226,0.00005543309,0.000001554288,4.211424e-8,0.0001319025,0.0001925644,0.9968477,0.002283946],"study_design_scores_gemma":[0.0003230366,0.00003490663,0.000004551705,0.0003163036,0.0001002448,0.00003289101,0.000004724458,6.123645e-7,0.0007376545,0.001148904,0.9968899,0.0004062927],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003142883,0.0002118644,0.0005243893,0.0007931807,0.0000677888,0.0001225489,0.9947491,0.0002934196,0.003206223],"genre_scores_gemma":[0.0001515304,0.001998049,0.0001114934,0.0000970721,0.0008858814,0.00007166489,0.9933788,0.00005045167,0.003255017],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04685617,"threshold_uncertainty_score":0.999927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0140957384188851,"score_gpt":0.3742947510687678,"score_spread":0.3601990126498827,"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."}}