{"id":"W2057691919","doi":"10.1002/jms.993","title":"Mass spectrometric characterization of efaproxiral (RSR13) and its implementation into doping controls using liquid chromatography–atmospheric pressure ionization‐tandem mass spectrometry","year":2006,"lang":"en","type":"article","venue":"Journal of Mass Spectrometry","topic":"Hormonal and reproductive studies","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Sporthochschule Köln; Universität zu Köln; World Anti-Doping Agency","keywords":"Chemistry; Mass spectrometry; Electrospray ionization; Tandem mass spectrometry; Orbitrap; Chromatography; Formic acid; Collision-induced dissociation; Direct electron ionization liquid chromatography–mass spectrometry interface; Atmospheric-pressure chemical ionization; Analytical Chemistry (journal); Fragmentation (computing); Extractive electrospray ionization; Ionization; Chemical ionization; Electron ionization; Protein mass spectrometry; Ion; Organic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001134212,0.0006363838,0.0004039719,0.001006455,0.0005277812,0.0004423905,0.0004872664,0.0009064646,0.001226368],"category_scores_gemma":[0.002382776,0.0002432551,0.0002909409,0.000516026,0.0004901058,0.0002582343,0.0002103707,0.0006279312,0.0005919904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000354037,"about_ca_system_score_gemma":0.0008833089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001607324,"about_ca_topic_score_gemma":0.002288493,"domain_scores_codex":[0.9986711,0.0002629344,0.0001022424,0.000280993,0.0006051595,0.00007769575],"domain_scores_gemma":[0.9993103,0.0001782664,0.0001505666,0.00005690347,0.0002256071,0.00007840668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002935762,0.0001280565,0.001230809,0.00006340752,0.00002611869,0.000118605,0.00003561656,0.00011616,0.9857017,0.0001089743,0.0000925467,0.01208463],"study_design_scores_gemma":[0.00005879791,0.0009140284,0.01203802,0.00002502832,0.00005585902,0.0009269523,0.0000307723,0.001733063,0.9811478,0.00006149322,0.002983107,0.00002496088],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9093387,0.007266541,0.07096292,0.0004541128,0.0001688279,0.0007987026,0.002619943,0.001008222,0.00738212],"genre_scores_gemma":[0.9150375,0.002413221,0.07476871,0.0005119927,0.00007199526,0.0003339998,0.002364535,0.0001155988,0.004382445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001607324,"threshold_uncertainty_score":0.005998373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01031253766969307,"score_gpt":0.2691784703687241,"score_spread":0.258865932699031,"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."}}