{"id":"W4399784086","doi":"10.1021/acs.macromol.3c02262","title":"Using Probability Models to Design the Microstructure of Linear Olefin Block Copolymers","year":2024,"lang":"en","type":"article","venue":"Macromolecules","topic":"Polymer crystallization and properties","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Research Council of Thailand; Thailand Research Fund","keywords":"Copolymer; Materials science; Olefin fiber; Microstructure; Polymer; Thermoplastic elastomer; Monte Carlo method; Molar mass distribution; Population; Elastomer; Polymer chemistry; Thermodynamics; Composite material; Mathematics; Physics","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":[0.000276824,0.0001295866,0.0001378267,0.0000456391,0.0001242683,0.0001132757,0.0002672109,0.00005014705,0.0001396095],"category_scores_gemma":[0.00002615013,0.00008137653,0.00005296008,0.0002295158,0.0001705309,0.00008568501,0.0001007313,0.00006403273,0.00002364503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002604719,"about_ca_system_score_gemma":0.0001195276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000166152,"about_ca_topic_score_gemma":0.000009553463,"domain_scores_codex":[0.9989755,0.0001493071,0.0002277437,0.0002525765,0.0001900435,0.0002048302],"domain_scores_gemma":[0.9995496,0.00004714616,0.00003629612,0.000258397,0.00005270057,0.00005581182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002948088,0.000009186949,0.000003200147,0.0000662028,0.000007829573,0.000003723924,0.00183001,0.02161442,0.9747217,0.001346749,0.000136942,0.000230498],"study_design_scores_gemma":[0.00005165152,0.00003450002,0.00000468589,0.00006846501,0.00001889677,0.00001985419,0.000122165,0.04744371,0.9486054,0.002970813,0.000543093,0.00011672],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8546973,0.003451009,0.1399146,0.0005459972,0.0003539593,0.0004438271,0.0001023993,0.0001232688,0.0003676226],"genre_scores_gemma":[0.9821922,0.000007524382,0.01730051,0.0003019162,0.00003513828,0.00000960427,0.000002013403,0.00002011261,0.0001309579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1274949,"threshold_uncertainty_score":0.3318439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07180298801995831,"score_gpt":0.2778641777121386,"score_spread":0.2060611896921803,"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."}}