{"id":"W4380740965","doi":"10.1117/12.2664911","title":"Artificial intelligence, machine learning and deep learning in plasma and microplasma spectrochemistry","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Microplasma; Spectrometer; Inductively coupled plasma; Plasma; Artificial neural network; Computer science; Spectroscopy; Optical fiber; Artificial intelligence; Materials science; Physics; Optics; Telecommunications; Astronomy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003796956,0.0001366564,0.0001426486,0.0001092272,0.00004442408,0.00002455005,0.00005967006,0.0001159732,0.00002934181],"category_scores_gemma":[0.0001692595,0.0001395558,0.00001310343,0.0003199526,0.0000739224,0.00004835601,0.00008750151,0.0005355911,0.00002637159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000320484,"about_ca_system_score_gemma":7.828095e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004122208,"about_ca_topic_score_gemma":0.0000351686,"domain_scores_codex":[0.9992875,0.000005186438,0.0001686551,0.0001990606,0.00006019676,0.000279337],"domain_scores_gemma":[0.9997582,0.0001225431,0.00001479521,0.00005818069,0.000005986443,0.00004024422],"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":[0.000007800822,0.000003673492,0.005077526,0.00005569635,0.000008076939,0.00002985762,0.00009395379,0.02010024,0.8805236,0.0002674824,0.000005182274,0.09382696],"study_design_scores_gemma":[0.00003812886,0.0000126539,0.0001018055,0.00001272215,0.000002118139,0.00001944669,0.0006322926,0.2354318,0.7609796,0.001810131,0.0008067203,0.0001525397],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949639,0.000324042,0.001256335,0.00007061712,0.00002127286,0.0000425186,5.861428e-7,0.00164534,0.001675338],"genre_scores_gemma":[0.9961809,0.001238081,0.002246198,0.000002525131,0.00001795586,0.000005130124,0.000006715246,0.00002541544,0.0002770724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2153316,"threshold_uncertainty_score":0.5690922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008785704637687184,"score_gpt":0.2188776517839681,"score_spread":0.210091947146281,"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."}}