{"id":"W3115609501","doi":"10.1103/physrevc.103.034329","title":"Investigation of pair-correlated <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:msup><mml:mn>0</mml:mn><mml:mo>+</mml:mo></mml:msup></mml:math> states in <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mmultiscripts><mml:mi>Ba</mml:mi><mml:mprescripts/><mml:none/><mml:mn>134</mml:mn></mml:mmultiscripts></mml:math> via the <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mrow><mml:mmultiscripts><mml:mi>Ba</mml:mi><mml:mprescripts/><mml:none/><mml:mn>136</mml:mn></mml:mmultiscripts><mml:mo>(</mml:mo><mml:mi>p</mml:mi><mml:mo>,</mml:mo><mml:mi>t</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math> reaction","year":2021,"lang":"lv","type":"article","venue":"Physical review. C","topic":"Nuclear physics research studies","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"TRIUMF; University of Guelph","funders":"National Research Foundation","keywords":"Algorithm; Artificial intelligence; Computer science","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":[0.006405581,0.000893452,0.001160524,0.00229946,0.002801722,0.005042533,0.002791638,0.001099722,0.03478933],"category_scores_gemma":[0.04811628,0.000672599,0.001562326,0.004414072,0.001701698,0.006221387,0.003869308,0.002746723,0.01028711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002009093,"about_ca_system_score_gemma":0.003945594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01061327,"about_ca_topic_score_gemma":0.01128487,"domain_scores_codex":[0.9919659,0.002578744,0.0003887714,0.002304088,0.001819539,0.0009429602],"domain_scores_gemma":[0.9690544,0.01082186,0.002311182,0.007663263,0.009230221,0.0009190703],"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":[0.001735772,0.0007470084,0.1801046,0.001232427,0.0008828148,0.003123885,0.009968413,0.01950354,0.00577389,0.4783958,0.103998,0.1945338],"study_design_scores_gemma":[0.0001666022,0.0005793621,0.08304383,0.0006789008,0.0007797961,0.002982552,0.01274446,0.3180948,0.03415102,0.3770404,0.1693227,0.0004155567],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3200398,0.001796095,0.4785018,0.002588386,0.001651227,0.0005601986,0.01358109,0.005090866,0.1761905],"genre_scores_gemma":[0.9073964,0.0004132287,0.05252913,0.0005647353,0.0001153025,0.0004050908,0.01240879,0.001583016,0.02458425],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03478933,"threshold_uncertainty_score":0.1163819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0253686829054891,"score_gpt":0.2625227981127273,"score_spread":0.2371541152072382,"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."}}