{"id":"W2901624631","doi":"10.15278/isms.2018.ti08","title":"DEVELOPMENT OF A HYBRID LASER-MASS SPECTROMETER WITH TWO INSTRUMENT ARMS: IRMPD AND HENDI COLD ION SPECTROSCOPIC EXPERIMENTS","year":2018,"lang":"en","type":"article","venue":"Proceedings of the 73rd International Symposium on Molecular Spectroscopy","topic":"Laser Design and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Infrared multiphoton dissociation; Mass spectrometry; Ion; Spectrometer; Laser; Materials science; Optics; Physics","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":[0.001745146,0.0007575293,0.0009415577,0.001197647,0.0008607272,0.0009514259,0.003538121,0.001194291,0.007031214],"category_scores_gemma":[0.0005975267,0.001183123,0.0004365258,0.0009033215,0.0006544305,0.001576138,0.001900692,0.001158811,0.002752685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001135328,"about_ca_system_score_gemma":0.000927184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009847193,"about_ca_topic_score_gemma":0.002316015,"domain_scores_codex":[0.9980785,0.0001698605,0.00006493789,0.0008211703,0.0006858321,0.0001797857],"domain_scores_gemma":[0.9995505,0.0001072318,0.00004692323,0.00009644196,0.0001154974,0.00008337884],"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":[0.0005820463,0.0003164596,0.005437185,0.0001550159,0.00008471899,0.0001697593,0.00008988761,0.001433298,0.9444628,0.003945674,0.001440609,0.0418826],"study_design_scores_gemma":[0.0004835861,0.001570538,0.01045447,0.00004317084,0.0001273744,0.001086121,0.0001059237,0.04798242,0.9034964,0.001448601,0.03299074,0.0002106564],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4130599,0.001280407,0.5479356,0.0008147512,0.0003510084,0.002125022,0.004512803,0.01152046,0.01840008],"genre_scores_gemma":[0.3292834,0.0003188214,0.652863,0.0006681205,0.0001202133,0.001487302,0.001700134,0.0004355698,0.01312349],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007031214,"threshold_uncertainty_score":0.02352172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00715816731042138,"score_gpt":0.2301133186781081,"score_spread":0.2229551513676867,"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."}}