{"id":"W2904647663","doi":"","title":"Language shift in slow motion: evidence from German-Canadian family papers","year":2018,"lang":"en","type":"article","venue":"Publication Server of the Institute for German Language (Institute for German Language)","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"German; Immigration; TRACE (psycholinguistics); Motion (physics); Language shift; Linguistics; Political science; Genealogy; History; Sociology; Computer science; Artificial intelligence; Law","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":[0.002494469,0.0003554684,0.0004300249,0.003848467,0.008934584,0.002336439,0.001229931,0.0005214578,0.005633371],"category_scores_gemma":[0.01125815,0.0002719235,0.0002071858,0.00785344,0.003107782,0.0007236997,0.001708933,0.0005485305,0.0004287202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009456332,"about_ca_system_score_gemma":0.009351423,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9523718,"about_ca_topic_score_gemma":0.9714248,"domain_scores_codex":[0.9976311,0.000468967,0.0001198544,0.0005404602,0.0007079354,0.0005315935],"domain_scores_gemma":[0.9892942,0.002386883,0.002057326,0.0009528603,0.004548199,0.0007605132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005616472,0.00007515846,0.6815258,0.0003698477,0.0002356278,0.002421103,0.2513995,0.0001941701,0.002299155,0.00538082,0.005779606,0.04975756],"study_design_scores_gemma":[0.00001318574,0.00003813507,0.871696,0.0001997752,0.00007504905,0.0007245693,0.1071533,0.0001122702,0.0007277699,0.0003757599,0.01882877,0.00005541951],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867466,0.001986364,0.0002552313,0.0003500633,0.0000232769,0.00002457966,0.001026121,0.000005238594,0.009582541],"genre_scores_gemma":[0.9965522,0.0007669795,0.0001931482,0.0000839048,0.000007066952,0.000009355283,0.0004146449,0.000008135967,0.001964549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04762822,"threshold_uncertainty_score":0.09581739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03048654467472237,"score_gpt":0.3332865031026183,"score_spread":0.3027999584278959,"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."}}