{"id":"W3176210669","doi":"10.1109/cefc46938.2020.9451362","title":"Transfer Learning for Efficiency Map Prediction","year":2020,"lang":"en","type":"article","venue":"","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Computation; Artificial intelligence; Transfer of learning; Artificial neural network; Network topology; Deep learning; Machine learning; Torque; Reduction (mathematics); Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005010122,0.00006908015,0.00006570531,0.00002096719,0.00003285468,0.0000112771,0.00006038759,0.00003592035,0.00004189642],"category_scores_gemma":[0.000042432,0.00006922553,0.00002994067,0.00007586786,0.00001059322,0.00008369514,0.000005172713,0.0001000897,0.00001221957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001919833,"about_ca_system_score_gemma":0.000003877917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001559798,"about_ca_topic_score_gemma":2.216725e-7,"domain_scores_codex":[0.9996363,0.000005475994,0.00009029221,0.00009976571,0.00005266723,0.0001155136],"domain_scores_gemma":[0.9998543,0.000039771,0.000002990067,0.00004348997,0.00001931614,0.00004016788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004146292,0.00002994879,0.008192316,0.0008439066,0.00006347859,0.000003726672,0.00177384,0.04320263,0.848883,0.07774561,0.009134048,0.010086],"study_design_scores_gemma":[0.0009092236,0.0009046858,0.00227548,0.00006980956,0.00004705459,0.000007900749,0.0001662241,0.7379262,0.2208747,0.02377645,0.01244263,0.0005996191],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0919271,0.00001976195,0.8926828,0.0001391936,0.00007087252,0.0001936832,0.000002818899,0.003981456,0.01098234],"genre_scores_gemma":[0.8375005,0.000001900018,0.1623081,0.00004258766,0.00007337071,0.00002950615,0.000004313056,0.00002511328,0.00001458826],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7455735,"threshold_uncertainty_score":0.2822936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01845407347288023,"score_gpt":0.2208384609933033,"score_spread":0.2023843875204231,"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."}}