{"id":"W2622325340","doi":"10.1177/1532440017713314","title":"A Squire Index Update","year":2017,"lang":"en","type":"article","venue":"State Politics & Policy Quarterly","topic":"Judicial and Constitutional Studies","field":"Social Sciences","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Squire; Measure (data warehouse); Legislature; Session (web analytics); Index (typography); Quarter (Canadian coin); Professionalization; Political science; Computer science; Law; Geography; Data mining; Linguistics; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01234585,0.001497469,0.001383504,0.02259369,0.001784288,0.008731869,0.001995326,0.001831907,0.1589707],"category_scores_gemma":[0.08008074,0.0007826695,0.001266874,0.0156798,0.0007629596,0.00749808,0.004193378,0.003020181,0.148811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004209062,"about_ca_system_score_gemma":0.005639873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01606312,"about_ca_topic_score_gemma":0.0163316,"domain_scores_codex":[0.9908513,0.001003459,0.001304973,0.0005622405,0.00569533,0.0005826727],"domain_scores_gemma":[0.9009447,0.007955426,0.005487342,0.00540264,0.07519992,0.005010097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00004661133,0.00003277503,0.001602004,0.0002275331,0.00001150365,0.00001975099,0.000041062,0.00005574242,0.00006262509,0.0019785,0.9415606,0.05436118],"study_design_scores_gemma":[0.00001767791,0.00003221596,0.005083825,0.0004107179,0.000009854141,0.00004348535,0.00005072156,0.00009381351,0.0001084431,0.0009382609,0.9931919,0.00001914499],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.006900785,0.0153022,0.007321571,0.0787647,0.04566295,0.001289263,0.2781711,0.008840247,0.5577472],"genre_scores_gemma":[0.03365301,0.01753343,0.01935366,0.02110386,0.02982946,0.002899719,0.3254946,0.006784121,0.5433481],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1589707,"threshold_uncertainty_score":0.5318101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0261224248769182,"score_gpt":0.3540305868266478,"score_spread":0.3279081619497296,"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."}}