{"id":"W2893392088","doi":"10.1101/424697","title":"Cross-linking/Mass Spectrometry: A Community-Wide, Comparative Study Towards Establishing Best Practice Guidelines","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"IONICS Mass Spectrometry (Canada); University of Victoria; University of Calgary; McGill University; Genome British Columbia; Jewish General Hospital","funders":"","keywords":"Harmonization; Status quo; Field (mathematics); Computer science; Data science; Best practice; Political science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3666605,0.0009104902,0.001632353,0.01274136,0.002705646,0.009701299,0.006241962,0.004009152,0.002640173],"category_scores_gemma":[0.3232438,0.0006138172,0.001194691,0.01119479,0.004478265,0.006424111,0.008716772,0.00203194,0.0009599567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006134471,"about_ca_system_score_gemma":0.02486075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004565938,"about_ca_topic_score_gemma":0.004157142,"domain_scores_codex":[0.6943645,0.1965048,0.04065349,0.01325833,0.05226398,0.002954862],"domain_scores_gemma":[0.5763282,0.1923458,0.0413471,0.03818031,0.1426884,0.009110209],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00141172,0.002129736,0.1020814,0.02070966,0.001212338,0.001154417,0.03034392,0.00221421,0.0154617,0.0217924,0.03023406,0.7712545],"study_design_scores_gemma":[0.0009573872,0.005144554,0.3311301,0.06306205,0.002815455,0.004928952,0.09181736,0.01757544,0.03943816,0.03449909,0.4078229,0.0008084984],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4616819,0.09607543,0.3019087,0.0751751,0.002273197,0.01464811,0.005498871,0.002849348,0.03988931],"genre_scores_gemma":[0.6206258,0.01524293,0.3450163,0.007219901,0.0003133515,0.005125847,0.003723193,0.0008168438,0.001915776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6333395,"threshold_uncertainty_score":0.7810204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0498559519841598,"score_gpt":0.3362189951863512,"score_spread":0.2863630432021914,"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."}}