{"id":"W1991841581","doi":"10.1103/physrevlett.100.062501","title":"Shell Model Description of the<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"><mml:mmultiscripts><mml:mi mathvariant=\"normal\">C</mml:mi><mml:mprescripts/><mml:none/><mml:mn>14</mml:mn></mml:mmultiscripts></mml:math>Dating<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"><mml:mi>β</mml:mi></mml:math>Decay with Brown-Rho-Scaled<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"><mml:mi>N</mml:mi><mml:mi>N</mml:mi></mml:math>Interactions","year":2008,"lang":"lv","type":"article","venue":"Physical Review Letters","topic":"Nuclear physics research studies","field":"Physics and Astronomy","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"TRIUMF","funders":"","keywords":"Physics; Excited state; Multiplet; Nucleon; Ground state; Particle physics; Atomic physics; Machine learning; Quantum mechanics; 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":[0.0003768675,0.001276509,0.0009070102,0.0005154081,0.0007422726,0.001656272,0.003334432,0.001764923,0.1580225],"category_scores_gemma":[0.001149756,0.0006132471,0.001064095,0.000846225,0.0002319286,0.001456969,0.0005991085,0.001832096,0.03894831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001077908,"about_ca_system_score_gemma":0.001503366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01574052,"about_ca_topic_score_gemma":0.01236273,"domain_scores_codex":[0.9997477,0.00004268971,0.00001609105,0.00002850851,0.0001182151,0.00004674256],"domain_scores_gemma":[0.9995046,0.0001323409,0.00003486396,0.0001314563,0.0001546677,0.00004205589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003843607,0.0003593962,0.001831076,0.0006333278,0.0001140705,0.0006383559,0.0004024483,0.3228301,0.02303783,0.2469963,0.3665297,0.03624316],"study_design_scores_gemma":[0.0001612498,0.00007526649,0.0009210754,0.00005053596,0.00003142023,0.0001831684,0.00009851393,0.673336,0.009822144,0.03899086,0.2762271,0.0001026343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02254929,0.0002738664,0.4680141,0.001346884,0.0005208384,0.0005016695,0.09355816,0.04135408,0.3718812],"genre_scores_gemma":[0.2854212,0.0007851669,0.3044803,0.001666366,0.0002448224,0.002824875,0.1243421,0.04720888,0.2330262],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1580225,"threshold_uncertainty_score":0.5286378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02674827735199711,"score_gpt":0.2629636832884931,"score_spread":0.236215405936496,"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."}}