{"id":"W2952513682","doi":"10.48550/arxiv.cond-mat/0610323","title":"Ab initio study of ladder-type polymers polythiophene and polypyrrole","year":2006,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Conducting polymers and applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Regroupement Québécois sur les Matériaux de Pointe","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Polythiophene; Polypyrrole; Thiophene; Ab initio; Polymer; Materials science; Pyrrole; Conductive polymer; Band gap; Charge density; Computational chemistry; Polymer chemistry; Chemical physics; Chemistry; Organic chemistry; Polymerization; Optoelectronics; Composite material; Physics; Quantum mechanics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001445883,0.0002554825,0.0003648471,0.000184705,0.0001857195,0.00004954815,0.0004470974,0.0001717898,0.000276764],"category_scores_gemma":[0.000014408,0.0002928911,0.0000715071,0.0003512734,0.0002151068,0.0001002084,0.0007093331,0.0002533478,0.00002602811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004494442,"about_ca_system_score_gemma":0.0001223065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005766592,"about_ca_topic_score_gemma":0.0003295196,"domain_scores_codex":[0.9985326,0.00009231716,0.0002606272,0.0007572643,0.00009474976,0.0002624227],"domain_scores_gemma":[0.9986812,0.000070685,0.000329779,0.0007099626,0.00009801293,0.0001103339],"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":[0.000767677,0.006640069,0.07214203,0.0006995683,0.0006368011,0.0004313428,0.006702506,0.03172891,0.8453625,0.02862071,0.002654617,0.003613309],"study_design_scores_gemma":[0.02244575,0.004985298,0.1573218,0.001308645,0.00671655,0.0001082255,0.05873743,0.0171133,0.6648241,0.05094397,0.003895493,0.01159945],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963387,0.0002320841,0.0002351078,0.00004751361,0.0003179547,0.0003647527,0.00007075717,0.00009585396,0.002297337],"genre_scores_gemma":[0.9979783,0.00004001648,0.00008117426,0.0000316655,0.00007294618,0.000001751545,0.00002006827,0.00002400989,0.001750074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1805384,"threshold_uncertainty_score":0.9999523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07808293538967216,"score_gpt":0.2074155945148075,"score_spread":0.1293326591251353,"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."}}