{"id":"W4254131083","doi":"10.1515/iupac.85.0497","title":"Interaction Distance","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":"Terminology; Chemical nomenclature; Mass spectrometry; Chemistry; Standardization; Accelerator mass spectrometry; Analytical Chemistry (journal); Computer science; Environmental chemistry; Chromatography; Linguistics; Organic chemistry","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":[0.001239027,0.002462515,0.001705382,0.005024968,0.001450203,0.004268873,0.003176294,0.001779442,0.1614286],"category_scores_gemma":[0.01390417,0.0006545447,0.002388858,0.008263262,0.0004026762,0.003848398,0.003032737,0.002344436,0.2316874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001827632,"about_ca_system_score_gemma":0.003664539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01937697,"about_ca_topic_score_gemma":0.03646135,"domain_scores_codex":[0.9969214,0.0004792333,0.0004024513,0.0009980395,0.0008817004,0.0003172121],"domain_scores_gemma":[0.9955355,0.001281802,0.0003398325,0.001359666,0.001210113,0.0002730293],"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":[0.00007961645,0.0000225352,0.001067397,0.000934308,0.00005551248,0.00002207094,0.00002821514,0.0002960602,0.00008383269,0.001345703,0.9855691,0.01049563],"study_design_scores_gemma":[0.00005988191,0.00001308476,0.001862907,0.0003362324,0.00002761126,0.00006793642,0.00007689166,0.0003256737,0.0002422591,0.003026364,0.9939368,0.00002429687],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001451525,0.0003358332,0.0003507935,0.000154803,0.00006736418,0.000022221,0.9952365,0.0009807639,0.002706668],"genre_scores_gemma":[0.0005400893,0.0002940534,0.0008563378,0.0001164061,0.00001491913,0.00008257269,0.9961861,0.0001799227,0.001729639],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1614286,"threshold_uncertainty_score":0.5400324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187358227895137,"score_gpt":0.3976117416300145,"score_spread":0.3857381593510631,"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."}}