{"id":"W2791012295","doi":"10.18438/eblip29330","title":"Norwegian Public Library Language Cafés Facilitate Discourse Between Immigrants and Norwegian-Born Citizens","year":2018,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Social Media and Politics","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Norwegian; Immigration; Conversation; Politics; Sociology; Political science; Media studies; Linguistics; Law; Communication","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005520318,0.0004479862,0.0003532877,0.00177655,0.005964732,0.005727547,0.0007012011,0.0009861046,0.01868916],"category_scores_gemma":[0.01015073,0.0002325744,0.0004801098,0.001500268,0.002752962,0.004647264,0.006481636,0.0005478865,0.001745341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003394302,"about_ca_system_score_gemma":0.004340694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01927237,"about_ca_topic_score_gemma":0.0372776,"domain_scores_codex":[0.9966515,0.002292801,0.0001681696,0.0002355608,0.0003069624,0.0003450077],"domain_scores_gemma":[0.9939601,0.003717832,0.0006588626,0.0002353283,0.0006331104,0.0007947559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0008365636,0.0002491297,0.04544238,0.002791744,0.00005642807,0.003004264,0.734588,0.0001280122,0.002751012,0.005009036,0.02956922,0.1755743],"study_design_scores_gemma":[0.00006007131,0.0001994089,0.04190931,0.001897885,0.00007337061,0.0005099073,0.6308101,0.0001191945,0.0009390874,0.0009346459,0.3224907,0.00005642381],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8829399,0.01247425,0.001556169,0.007107846,0.0005674459,0.0001104927,0.0003881041,0.0001835752,0.09467219],"genre_scores_gemma":[0.9832008,0.002930227,0.001421948,0.0007946381,0.0001293594,0.00008171645,0.0001582175,0.00008084842,0.01120223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01927237,"threshold_uncertainty_score":0.06252146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02871690930143276,"score_gpt":0.3126619252135602,"score_spread":0.2839450159121275,"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."}}