{"id":"W4396929933","doi":"10.1080/08989575.2024.2337576","title":"Gathering Stories for Community Action","year":2024,"lang":"en","type":"article","venue":"a/b Auto/Biography Studies","topic":"Digital Storytelling and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Andrew W. Mellon Foundation; Modern Language Association; National Endowment for the Humanities","keywords":"Storytelling; Media studies; Politics; Session (web analytics); Active listening; Visual arts; Sociology; Library science; History; Political science; Narrative; Law; Art; World Wide Web; Computer science","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006976232,0.0001382589,0.0001923101,0.0001978282,0.001890912,0.00003261147,0.00009827354,0.00008298094,0.00001240443],"category_scores_gemma":[0.0001843726,0.0001158974,0.0001572763,0.0004345665,0.0001178262,0.0002123839,0.00005320245,0.0004255286,0.00006766387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001139753,"about_ca_system_score_gemma":0.0000600495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003419367,"about_ca_topic_score_gemma":0.0003099529,"domain_scores_codex":[0.9990165,0.0001569496,0.000247491,0.0001668026,0.0001011769,0.0003111049],"domain_scores_gemma":[0.9981655,0.001359012,0.00006034358,0.0002057942,0.0001647282,0.00004461833],"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":[0.0001235146,0.0003377093,0.03832796,0.007389314,0.002298393,0.000002382577,0.304625,0.00001931894,0.0008000369,0.02380083,0.4378364,0.1844391],"study_design_scores_gemma":[0.0001580515,0.0001397736,0.01247758,0.0006789968,0.00009567013,5.644713e-7,0.1143481,0.00005157826,0.00009297003,0.01381962,0.8579246,0.0002124359],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9237353,0.03342165,0.00243929,0.0027232,0.01930612,0.00118882,0.00009523641,0.001830544,0.01525982],"genre_scores_gemma":[0.9935274,0.001339912,0.0004067087,0.0001949377,0.0006304721,0.0004740714,0.0000270508,0.00003062682,0.003368864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4200882,"threshold_uncertainty_score":0.9994085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.319981130458675,"score_gpt":0.5143708610791954,"score_spread":0.1943897306205204,"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."}}