{"id":"W2566725133","doi":"","title":"Digital pencil sharpening: technology integration and language learning autonomy","year":2014,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Education and Technology Integration","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Linguistic Association","funders":"","keywords":"Interactive whiteboard; Autonomy; Computer science; Sharpening; Mathematics education; Pedagogy; Language acquisition; Technology integration; Teaching method; Psychology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002358346,0.0003917266,0.0002732568,0.0008713976,0.001387164,0.007506267,0.000673532,0.001107577,0.004925216],"category_scores_gemma":[0.005970134,0.0002085235,0.0003167596,0.0007639778,0.01475273,0.008145432,0.005169035,0.001866391,0.0004687709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001378158,"about_ca_system_score_gemma":0.001254885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005869748,"about_ca_topic_score_gemma":0.0003615737,"domain_scores_codex":[0.9969138,0.001683363,0.0001246195,0.0003375166,0.0007250215,0.0002156169],"domain_scores_gemma":[0.99621,0.002381064,0.0004339405,0.0005149018,0.0002459476,0.0002141526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00005188041,0.00006337756,0.001169874,0.0001476528,0.000007886047,0.0005117254,0.05651163,0.0008233857,0.001925433,0.8665563,0.0007421324,0.07148868],"study_design_scores_gemma":[0.00009189302,0.0002868259,0.003965642,0.0003869995,0.00002550118,0.00197695,0.03300713,0.005213698,0.01057136,0.6733221,0.2710912,0.00006068141],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2606993,0.003921019,0.1794819,0.007295311,0.0002272007,0.000111214,0.00004037954,0.0002828381,0.5479409],"genre_scores_gemma":[0.9675436,0.0008585487,0.01067926,0.0002875049,0.00004521708,0.00006270566,0.00001601399,0.00003304772,0.02047413],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007506267,"threshold_uncertainty_score":0.01647651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01350885532835143,"score_gpt":0.2661034930253696,"score_spread":0.2525946376970182,"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."}}