{"id":"W2005672872","doi":"10.1016/j.chroma.2004.11.008","title":"Towards smaller and faster gas chromatography–mass spectrometry systems for field chemical detection","year":2004,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":60,"is_retracted":false,"has_abstract":false,"ca_institutions":"Defence Research and Development Canada","funders":"Defence Science and Technology Group; Defence Research and Development Canada","keywords":"Chemistry; Chromatography; Mass spectrometry; Gas chromatography; Gas chromatography–mass spectrometry; Analytical Chemistry (journal)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004622618,0.0003286145,0.0006319136,0.0003290719,0.00008981274,0.0001221887,0.0002972649,0.0003297951,0.00009343574],"category_scores_gemma":[0.0002234404,0.0002855415,0.0005822993,0.0004658065,0.0001281247,0.0001764481,0.00004753168,0.0004601846,0.000001404497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001215999,"about_ca_system_score_gemma":0.0001104675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001102482,"about_ca_topic_score_gemma":7.238435e-7,"domain_scores_codex":[0.9978258,0.00002168677,0.000885214,0.0003172287,0.0005159276,0.0004341469],"domain_scores_gemma":[0.9984015,0.0002162148,0.0005293438,0.0002516012,0.0002588334,0.0003424744],"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":[0.0002617255,0.0001621259,0.001581741,0.0009580996,0.0007341274,0.00005926241,0.0001335121,0.00001062725,0.9937016,0.0002480655,0.0001411809,0.002007959],"study_design_scores_gemma":[0.002448849,0.0002012271,0.0003635429,0.0004466101,0.0002132553,0.00115413,0.0003589441,0.00009543052,0.9880256,0.004411848,0.001880192,0.0004003905],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7613071,0.001823903,0.2337079,0.0003351904,0.0002465532,0.0001300435,0.000009906088,0.00006093247,0.00237848],"genre_scores_gemma":[0.9338778,0.0002663765,0.06520736,0.00007074825,0.0004898559,0.00002039585,0.000002729624,0.00004099312,0.00002375543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1725707,"threshold_uncertainty_score":0.9999596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01475740978172752,"score_gpt":0.2585689425579507,"score_spread":0.2438115327762231,"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."}}