{"id":"W4237024730","doi":"10.1515/iupac.68.0039","title":"Collision Cross Section","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Thermal and Kinetic Analysis","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Glossary; Terminology; Section (typography); Field (mathematics); Collision; Computer science; Linguistics; Philosophy; Programming language; Mathematics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006724436,0.0003270798,0.0005175545,0.0001399974,0.0002000686,0.0001641061,0.0004575477,0.0003615213,0.01602478],"category_scores_gemma":[0.0002417982,0.0002155326,0.0001820143,0.0001887982,0.0001909025,0.0001236696,0.0001889305,0.0002146231,0.00003298783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002917777,"about_ca_system_score_gemma":0.0002882905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003740675,"about_ca_topic_score_gemma":0.0005865388,"domain_scores_codex":[0.9974817,0.0001063423,0.0004582889,0.000540183,0.001040459,0.0003730315],"domain_scores_gemma":[0.9983556,0.00006212991,0.0003056836,0.0006781206,0.0004590774,0.0001393658],"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":[0.0001793614,0.00008783242,0.000005045833,0.00005030805,0.00002406324,0.00002270157,0.000006023579,0.00003069504,0.003316797,0.000002452649,0.9958256,0.0004490562],"study_design_scores_gemma":[0.000493633,0.0001373027,0.000058789,0.0001654433,0.0001131867,0.00001148986,0.000007938285,0.000006156186,0.002791357,0.00006963898,0.9958372,0.000307924],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01611134,0.0002466932,0.0004295646,0.000163756,0.001837451,0.0001369774,0.9809582,0.00007768955,0.00003837969],"genre_scores_gemma":[0.0002993655,0.0003174261,0.00004296068,0.0001257612,0.002014567,0.000009823596,0.9953226,0.00002479776,0.001842671],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0159918,"threshold_uncertainty_score":0.9848747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01138244899561572,"score_gpt":0.3877033123264578,"score_spread":0.3763208633308421,"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."}}