{"id":"W2328310335","doi":"10.1016/j.jqsrt.2016.04.004","title":"dParFit: A computer program for fitting diatomic molecule spectral data to parameterized level energy expressions","year":2016,"lang":"en","type":"article","venue":"Journal of Quantitative Spectroscopy and Radiative Transfer","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Solar Energy Technologies Office; Natural Sciences and Engineering Research Council of Canada","keywords":"Diatomic molecule; Isotopologue; Parameterized complexity; Semiclassical physics; Atomic physics; Physics; Quantum mechanics; Spectral line; Molecule; Mathematics; Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001015051,0.001941799,0.00124633,0.001322121,0.001086188,0.001122799,0.003864784,0.001196229,0.04610909],"category_scores_gemma":[0.002965946,0.001225981,0.001244276,0.001558523,0.0004494073,0.001552777,0.001059876,0.002771239,0.008777139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009339361,"about_ca_system_score_gemma":0.001479894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007126488,"about_ca_topic_score_gemma":0.007761326,"domain_scores_codex":[0.9996907,0.00005661874,0.00002949153,0.00008786166,0.0000855406,0.00004990691],"domain_scores_gemma":[0.9992368,0.0004438864,0.00004845527,0.00008427216,0.0001478442,0.0000387532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001551223,0.0007938285,0.007289918,0.002234231,0.0009929293,0.0009413718,0.001109948,0.2010593,0.0361525,0.03982065,0.3112655,0.3967887],"study_design_scores_gemma":[0.0003948424,0.00009474483,0.001377789,0.00006152617,0.0000999914,0.0002001571,0.0001050055,0.8627275,0.03790153,0.01204526,0.08487777,0.0001139141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.02306255,0.0002600898,0.6377146,0.0001894276,0.0001734586,0.0002275805,0.01730894,0.3130021,0.008061332],"genre_scores_gemma":[0.1374112,0.0005229383,0.7472534,0.000466371,0.00007808908,0.001741096,0.02702836,0.07212738,0.01337121],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04610909,"threshold_uncertainty_score":0.1542503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08216751063273342,"score_gpt":0.3317677954037405,"score_spread":0.249600284771007,"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."}}