{"id":"W2782534858","doi":"10.29173/iasl7472","title":"Motivation to transfer learning to multiple contexts","year":2021,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Online and Blended Learning","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Information literacy; Transfer of learning; Process (computing); Set (abstract data type); Computer science; Knowledge management; Mathematics education; Sanctions; Work (physics); Psychology; Pedagogy; Artificial intelligence; Political science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.002603813,0.000154376,0.0002031221,0.0004176134,0.0005310848,0.001958298,0.0003492524,0.0004579565,0.002585519],"category_scores_gemma":[0.009608404,0.0001050252,0.0002824627,0.0001571312,0.0006469492,0.0006159531,0.001925412,0.0006660596,0.0003020787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004364554,"about_ca_system_score_gemma":0.0006600205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005589302,"about_ca_topic_score_gemma":0.000576406,"domain_scores_codex":[0.9981176,0.0009141965,0.00008422226,0.0001739402,0.0004394926,0.0002705359],"domain_scores_gemma":[0.9951699,0.002493522,0.0006139966,0.0002909212,0.0004553141,0.0009762216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003476314,0.002716772,0.6777945,0.0003099499,0.0001668122,0.0006100027,0.04963149,0.001948118,0.01231169,0.006039554,0.001368834,0.2467546],"study_design_scores_gemma":[0.00007202811,0.001556271,0.9256024,0.0001535577,0.00008870482,0.0006145361,0.04352983,0.00633393,0.005068952,0.0044384,0.01245743,0.00008386205],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955708,0.00003779978,0.0008156071,0.0001281475,0.000004080854,0.0000452923,0.000008973236,0.000009827466,0.003379486],"genre_scores_gemma":[0.9987162,0.00003155299,0.0004277022,0.00002494118,0.000002571213,0.00002806133,0.0000100267,0.000002069638,0.0007567687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002603813,"threshold_uncertainty_score":0.01377046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03080269190109307,"score_gpt":0.3070393191372028,"score_spread":0.2762366272361097,"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."}}