{"id":"W4250146705","doi":"10.1515/iupac.85.0511","title":"Ionization Efficiency","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; Analytical Chemistry (journal); Computer science; Environmental chemistry; Chromatography; 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":[0.002019774,0.001998328,0.00174923,0.005559157,0.000908778,0.004384283,0.002453953,0.001332698,0.1184113],"category_scores_gemma":[0.01378323,0.0006082849,0.002474217,0.009709031,0.000340878,0.004044242,0.001858321,0.001807165,0.1979768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002111804,"about_ca_system_score_gemma":0.002559001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01306489,"about_ca_topic_score_gemma":0.01405557,"domain_scores_codex":[0.9964541,0.0004047533,0.0005858099,0.001050089,0.001215894,0.0002892741],"domain_scores_gemma":[0.9945583,0.001373647,0.0005570977,0.001280553,0.00207333,0.0001570044],"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":[0.0001359997,0.00002627857,0.002195422,0.001487235,0.00008561825,0.00002370537,0.00002666141,0.0005629421,0.0002593688,0.001462254,0.9670616,0.02667291],"study_design_scores_gemma":[0.00008269167,0.00001345414,0.004289912,0.0004265473,0.00005275129,0.00008293175,0.00004976809,0.0004473306,0.0006720619,0.002895827,0.9909489,0.00003789314],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003407403,0.0006564888,0.0006634286,0.0001563799,0.00009652037,0.00004491042,0.9901939,0.00140502,0.006442583],"genre_scores_gemma":[0.001444327,0.0008910448,0.002053555,0.0002188274,0.00003488487,0.0001471565,0.9908722,0.0004685704,0.003869424],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1184113,"threshold_uncertainty_score":0.3961254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00963439475734556,"score_gpt":0.3727519916647931,"score_spread":0.3631175969074475,"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."}}