{"id":"W2093501038","doi":"10.1007/s12043-010-0106-8","title":"The canonical and grand canonical models for nuclear multifragmentation","year":2010,"lang":"en","type":"article","venue":"Pramana","topic":"Astronomical and nuclear sciences","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Canonical ensemble; Microcanonical ensemble; Grand canonical ensemble; Observable; Statistical physics; Statistical ensemble; Physics; Canonical correlation; Computer science; Quantum mechanics; Monte Carlo method; Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001291171,0.00005575184,0.00005908476,0.000006470486,0.0003421499,0.0001072957,0.0001187533,0.00001939883,0.00005288204],"category_scores_gemma":[0.000004882695,0.00003590583,0.00003600089,0.00002108455,0.0001516186,0.0001139849,0.00004292754,0.0001054834,0.000008498083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003343989,"about_ca_system_score_gemma":0.00002216723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002427988,"about_ca_topic_score_gemma":0.0001206005,"domain_scores_codex":[0.9995546,0.000009822655,0.0000911301,0.0001371241,0.00005522848,0.0001521176],"domain_scores_gemma":[0.9996954,0.00009766592,0.00003237705,0.00008937511,0.00001479149,0.00007036785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007716339,0.00007308668,0.00410394,0.000003563337,0.00003567526,1.146879e-7,0.0003940718,0.0001473364,0.0017475,0.7065705,0.002376425,0.2844706],"study_design_scores_gemma":[0.002974101,0.0002845352,0.02196031,0.00001069626,0.0000832264,0.000002445835,0.001643011,0.4661916,0.0007703211,0.1265407,0.3789521,0.0005868883],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992436,0.0000123426,0.002498995,0.001518175,0.0001519557,0.0001727253,0.00001308863,0.00001289422,0.003183833],"genre_scores_gemma":[0.9975806,0.000001350441,0.00205657,0.00003600176,0.0001432155,0.00001090312,0.000003639787,0.000006789423,0.0001608646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5800298,"threshold_uncertainty_score":0.2631575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008525398215003947,"score_gpt":0.2387330778288113,"score_spread":0.2302076796138073,"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."}}