{"id":"W4411152581","doi":"10.1103/t91y-l6rf","title":"Coulomb excitation of <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mmultiscripts> <mml:mi>Sr</mml:mi> <mml:mprescripts/> <mml:none/> <mml:mn>80</mml:mn> </mml:mmultiscripts> </mml:math> and the limits of the <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mi>N</mml:mi> <mml:mo>≈</mml:mo> <mml:mi>Z</mml:mi> <mml:mo>≈</mml:mo> <mml:mn>40</mml:mn> </mml:mrow> </mml:math> island of deformation","year":2025,"lang":"lv","type":"article","venue":"Physical review. C","topic":"Nuclear physics research studies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; TRIUMF; University of Guelph; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Surrey; U.S. Department of Energy","keywords":"Algorithm; Computer science","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":[0.0008023037,0.0005888821,0.0005830228,0.001420313,0.001230337,0.003162449,0.001206071,0.001607666,0.1693123],"category_scores_gemma":[0.003697045,0.0003606114,0.0007852767,0.001413119,0.0009314154,0.003297335,0.001526404,0.001737413,0.0493953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00156564,"about_ca_system_score_gemma":0.001007118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005342967,"about_ca_topic_score_gemma":0.005080324,"domain_scores_codex":[0.9992301,0.000116733,0.00003895742,0.0001141196,0.0003796936,0.0001203399],"domain_scores_gemma":[0.9989661,0.000378621,0.00008958123,0.0002544789,0.0002406869,0.00007059531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002012372,0.00005682666,0.001055485,0.0004611275,0.00003179974,0.0004588827,0.0005758432,0.001039367,0.008711295,0.6895426,0.2316259,0.06623962],"study_design_scores_gemma":[0.00006151819,0.00008187315,0.003082695,0.0002753,0.00003196109,0.0005448279,0.0005181441,0.004778079,0.02858491,0.1251553,0.8368008,0.0000845843],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01449908,0.002065273,0.02769025,0.003716282,0.0009847741,0.00007464804,0.002759286,0.002676946,0.9455334],"genre_scores_gemma":[0.3233988,0.00368513,0.01655379,0.002763478,0.0003151117,0.0002647781,0.007640232,0.004829446,0.6405492],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1693123,"threshold_uncertainty_score":0.5664061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0226786342909689,"score_gpt":0.2755870133229502,"score_spread":0.2529083790319813,"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."}}