{"id":"W4391339902","doi":"10.26434/chemrxiv-2024-tkrc5","title":"How soft is your ESI-MS anyway?","year":2024,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Ottawa; National Research Council Canada; Trent University; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Trent University; Universities Space Research Association","keywords":"Business","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006342326,0.0018065,0.00138914,0.001895602,0.001463078,0.004294139,0.001819712,0.003029348,0.04879079],"category_scores_gemma":[0.01308642,0.0008856475,0.0008946685,0.001395645,0.001638959,0.007766391,0.002775447,0.002953066,0.05509498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007105261,"about_ca_system_score_gemma":0.001193584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004081838,"about_ca_topic_score_gemma":0.0007039976,"domain_scores_codex":[0.9952008,0.0008211368,0.0004129081,0.001012872,0.002187635,0.0003646637],"domain_scores_gemma":[0.9922023,0.002300919,0.0009160338,0.00155178,0.002098196,0.0009307503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001965042,0.000378425,0.009584974,0.00257575,0.0004032814,0.001637683,0.0008288658,0.0006177868,0.1949589,0.009768737,0.2559327,0.521348],"study_design_scores_gemma":[0.0001346003,0.0006477081,0.007511292,0.001005075,0.0001903893,0.005434934,0.0009538533,0.002885492,0.3142455,0.02123163,0.6452381,0.0005214092],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.118125,0.05442406,0.3859455,0.1347905,0.02724933,0.001394491,0.0168363,0.09227741,0.1689574],"genre_scores_gemma":[0.284822,0.03740293,0.379877,0.0813072,0.008753041,0.001820068,0.01216457,0.01818897,0.1756642],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04879079,"threshold_uncertainty_score":0.1632214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02607815130726068,"score_gpt":0.2811864134997964,"score_spread":0.2551082621925357,"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."}}