{"id":"W4396692992","doi":"10.1021/acs.jpca.4c00999","title":"The Role of Momentum Partitioning in Covariance Ion Imaging Analysis","year":2024,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry A","topic":"Ion-surface interactions and analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"SLAC National Accelerator Laboratory; H2020 European Research Council; Basic Energy Sciences; Jesus College, University of Oxford; Jesus College, University of Cambridge; Office of Science; Japan Society for the Promotion of Science; Academy of Finland; Helmholtz-Gemeinschaft; U.S. Department of Energy; Leverhulme Trust; University of Southampton; Engineering and Physical Sciences Research Council; UK Research and Innovation; National Science Foundation","keywords":"Fragmentation (computing); Dissociation (chemistry); Ion; Ionization; Extreme ultraviolet; Femtosecond; Covariance; Breakup; Physics; Chemical physics; Chemistry; Atomic physics; Laser; Optics; Quantum mechanics; Physical chemistry; Ecology; Statistics; Biology; Mathematics","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":[0.001421952,0.0004352325,0.0002719767,0.0006115789,0.000534217,0.0008388103,0.0006509247,0.0003853732,0.0008809986],"category_scores_gemma":[0.005615987,0.0002022308,0.0002454078,0.0005053857,0.0006968968,0.001515079,0.0006115994,0.0005093026,0.0001100406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000559126,"about_ca_system_score_gemma":0.0005975011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00219483,"about_ca_topic_score_gemma":0.002192881,"domain_scores_codex":[0.9996382,0.00007738429,0.00002171833,0.00007014027,0.0001309084,0.00006160747],"domain_scores_gemma":[0.9979789,0.001249868,0.0002497435,0.0002232627,0.0002305811,0.00006769483],"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":[0.001114161,0.0002136517,0.0286522,0.0001286403,0.00008285372,0.0004614854,0.0004828084,0.1303401,0.6936395,0.02391887,0.0004482264,0.1205176],"study_design_scores_gemma":[0.0000182094,0.0001219965,0.0153303,0.000008171196,0.00002310206,0.0002548057,0.0001023179,0.7842895,0.1933255,0.005648553,0.0008121483,0.00006539236],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6492282,0.0001627599,0.348451,0.0001514596,0.00001064972,0.00003634609,0.0001040437,0.0004394499,0.001416097],"genre_scores_gemma":[0.9366068,0.00006934112,0.06282246,0.00001828554,0.000003880871,0.00002060768,0.00009484435,0.00007814678,0.0002856632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00219483,"threshold_uncertainty_score":0.007520139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002192299621117528,"score_gpt":0.2148494180253533,"score_spread":0.2126571184042358,"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."}}