{"id":"W4312944424","doi":"10.37975/nas.42","title":"Canadian Political Storytelling: Back to a Future?","year":2021,"lang":"en","type":"article","venue":"New Area Studies","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Expansive; Scholarship; Politics; Storytelling; Field (mathematics); Work (physics); Space (punctuation); Political science; Sociology; Public relations; Media studies; Engineering ethics; Engineering; Narrative; Computer science; Law; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008486916,0.0000818228,0.0001452816,0.00004702773,0.0004272541,0.00005598189,0.0001223991,0.00005368382,0.0005481385],"category_scores_gemma":[0.00051203,0.00008742224,0.00004868929,0.000297412,0.00008603656,0.00006801461,0.00002728131,0.00007723398,0.0003845001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009822379,"about_ca_system_score_gemma":0.003756736,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8997262,"about_ca_topic_score_gemma":0.9980032,"domain_scores_codex":[0.998743,0.00004554592,0.0000914259,0.0001910776,0.0001913009,0.0007376315],"domain_scores_gemma":[0.9983953,0.00007943859,0.00001520625,0.0001355759,0.0001161516,0.001258322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001483833,0.000003713654,0.0006547817,0.000003665877,0.00002732479,0.0000508032,0.02148382,0.000001455457,0.00000317735,0.288742,0.6867277,0.002300046],"study_design_scores_gemma":[0.00006357348,0.000007793977,0.002929003,0.00001635789,0.000005651058,0.00000157964,0.01348068,2.570159e-7,0.00002548545,0.003360361,0.9800003,0.0001089979],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02005517,0.005717124,0.00002571309,0.691498,0.001436258,0.0001687592,0.0001785084,0.00003489967,0.2808855],"genre_scores_gemma":[0.6655391,0.0009269376,0.000825992,0.08174819,0.007089534,0.00001277218,0.00000290308,0.00002275539,0.2438318],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.645484,"threshold_uncertainty_score":0.6664288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05911894273725828,"score_gpt":0.3334621400746762,"score_spread":0.274343197337418,"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."}}