{"id":"W4385571207","doi":"10.18653/v1/2023.bea-1.3","title":"A Transfer Learning Pipeline for Educational Resource Discovery with Application in Survey Generation","year":2023,"lang":"en","type":"article","venue":"","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pipeline (software); George (robot); Chen; Transfer of learning; Computer science; Resource (disambiguation); Artificial intelligence; Data science; Programming language; Geology; Computer network","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":[0.005306501,0.001753673,0.001328559,0.006200698,0.001314152,0.002461858,0.002779442,0.002270937,0.0349631],"category_scores_gemma":[0.02207374,0.001176451,0.002211477,0.004813136,0.0005186776,0.003683853,0.00422883,0.002679237,0.02975079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001109617,"about_ca_system_score_gemma":0.002524154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008671123,"about_ca_topic_score_gemma":0.01708117,"domain_scores_codex":[0.9977462,0.0009060627,0.0001824752,0.0006207213,0.0003795247,0.0001650171],"domain_scores_gemma":[0.9913522,0.005753988,0.0001777551,0.001515024,0.0009279715,0.0002731878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005838469,0.0004799377,0.005001715,0.0005638315,0.0003729002,0.0002984081,0.0003626668,0.01342456,0.002991544,0.008217774,0.1789844,0.7887184],"study_design_scores_gemma":[0.0003683595,0.0001818129,0.002736171,0.0001167306,0.0001614763,0.0002348489,0.0003261337,0.8290475,0.00839272,0.06676348,0.0915906,0.00008018821],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006567431,0.0008769803,0.7623925,0.001051224,0.0002516746,0.0006214036,0.01372861,0.2100797,0.00443048],"genre_scores_gemma":[0.1105,0.0005612792,0.8200862,0.0006354894,0.0002312631,0.001854354,0.05198839,0.004475219,0.009667796],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0349631,"threshold_uncertainty_score":0.1169632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02556965356638426,"score_gpt":0.2878062985854368,"score_spread":0.2622366450190526,"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."}}