{"id":"W2041314074","doi":"10.1017/s0007123411000160","title":"Language and Ideology in Congress","year":2011,"lang":"en","type":"article","venue":"British Journal of Political Science","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Kellogg's (Canada)","funders":"","keywords":"Ideology; Legislature; Interpretation (philosophy); Political science; Politics; Law; Linguistics; Philosophy","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":[0.001724147,0.000137602,0.0002723724,0.004197621,0.001067097,0.003095388,0.0002103056,0.0003658635,0.006268361],"category_scores_gemma":[0.01356138,0.0001077635,0.0001818311,0.005410894,0.001282297,0.001013277,0.001291846,0.0006194997,0.0009624853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008814016,"about_ca_system_score_gemma":0.0006290037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002458527,"about_ca_topic_score_gemma":0.004007597,"domain_scores_codex":[0.9975016,0.001248173,0.0001962179,0.000246939,0.0005660599,0.0002411449],"domain_scores_gemma":[0.9893234,0.006638985,0.002695382,0.0002389617,0.0007750483,0.000328093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009254325,0.0003774277,0.6649885,0.0006516337,0.0002486448,0.002371716,0.1004723,0.001316938,0.004879212,0.02614229,0.01215539,0.1854705],"study_design_scores_gemma":[0.00001870508,0.0001049474,0.9375725,0.0003307005,0.00004468232,0.0006359175,0.03022526,0.001046854,0.0005850993,0.003411992,0.02597471,0.00004870081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978255,0.001674104,0.0002300751,0.0008862386,0.0000572876,0.000008511232,0.0005658733,0.000009103448,0.01831394],"genre_scores_gemma":[0.9971994,0.0005102429,0.0001847361,0.00006578738,0.00005834156,0.00001593692,0.0004007908,0.0000117339,0.001553026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006268361,"threshold_uncertainty_score":0.02096975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03988064428790917,"score_gpt":0.3808767252756357,"score_spread":0.3409960809877265,"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."}}