{"id":"W4406216502","doi":"10.3390/atoms13010006","title":"Exploring the Nuclear Chart via Precision Mass Spectrometry with the TITAN MR-TOF MS","year":2025,"lang":"en","type":"article","venue":"Atoms","topic":"Astronomical and nuclear sciences","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of British Columbia; McGill University; University of Calgary; University of Victoria; University of Waterloo; TRIUMF","funders":"Natural Sciences and Engineering Research Council of Canada; Justus Liebig Universität Gießen; Helmholtz Graduate School for Hadron and Ion Research; Deutsche Forschungsgemeinschaft; TRIUMF; Bundesministerium für Bildung und Forschung","keywords":"Nuclide; Physics; Nuclear astrophysics; Isotope; Titan (rocket family); Mass spectrometry; Nuclear physics; Nuclear engineering; Astrobiology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001263808,0.00008893621,0.00008752465,0.00002394397,0.0002944395,0.00008633344,0.0003665171,0.000009003308,0.0003848183],"category_scores_gemma":[0.000001158724,0.00004068927,0.00005362409,0.0002599399,0.0001215721,0.0001617434,0.00008849368,0.0001436225,0.0002255597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000134001,"about_ca_system_score_gemma":0.00001300323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006428304,"about_ca_topic_score_gemma":0.000002636448,"domain_scores_codex":[0.9994064,0.0000193204,0.00008583034,0.0001730963,0.0001236511,0.0001917218],"domain_scores_gemma":[0.9996052,0.00006404388,0.00003646297,0.0002484106,0.00001322669,0.00003262203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002282589,0.0002717364,0.08575216,0.00001472387,0.0004542047,0.000002896514,0.003325878,0.0002272331,0.01606184,0.4739432,0.01506728,0.4046506],"study_design_scores_gemma":[0.00157162,0.0006100283,0.4066006,0.0001929172,0.000175272,0.000002420139,0.01855442,0.01115452,0.01904759,0.03855873,0.5025501,0.0009818739],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9669739,0.00001453775,0.005705765,0.002708373,0.0001501152,0.0001135779,0.000002157571,0.00002384658,0.02430776],"genre_scores_gemma":[0.9981142,0.000001510558,0.0004721133,0.0001042572,0.0001646972,0.00001124437,8.841123e-7,0.000008000988,0.001123036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4874828,"threshold_uncertainty_score":0.4213491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0140553702072303,"score_gpt":0.2113975751346169,"score_spread":0.1973422049273866,"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."}}