{"id":"W1964505066","doi":"10.1007/s10994-008-5087-1","title":"Guest editor’s introduction: special issue on inductive transfer learning","year":2008,"lang":"en","type":"article","venue":"Machine Learning","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"Acadia University","funders":"","keywords":"Inductive transfer; Computer science; Transfer of learning; Multi-task learning; Artificial intelligence; Generalization; Task (project management); Heuristics; Machine learning; Representation (politics); Similarity (geometry); Transfer of training; Instance-based learning; Sequence learning; Active learning (machine learning); Robot learning; Knowledge management; Mathematics","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":[0.005073758,0.002200394,0.002833169,0.003228454,0.001556222,0.004259165,0.002822859,0.006184754,0.03294037],"category_scores_gemma":[0.02182945,0.0008742107,0.00192049,0.001513425,0.001254932,0.003648371,0.001777778,0.01094899,0.0183868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00114872,"about_ca_system_score_gemma":0.001421543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006132708,"about_ca_topic_score_gemma":0.001909724,"domain_scores_codex":[0.997234,0.0005446592,0.0004009317,0.0005486456,0.001062829,0.0002088503],"domain_scores_gemma":[0.9813024,0.005037873,0.001264582,0.001038386,0.009487377,0.001869437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003544115,0.00001480132,0.00006269522,0.0001443512,0.0000165097,0.00006660386,0.000004750478,0.00004729713,0.0001126906,0.0003624665,0.9885852,0.01054723],"study_design_scores_gemma":[0.00005232852,0.00005700917,0.0008590209,0.0002625677,0.00007010355,0.0005065184,0.00002178959,0.0007985173,0.0004554021,0.002873141,0.9940075,0.00003623171],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00007688312,0.003128055,0.001270039,0.03169038,0.9622361,0.0000129218,0.00007140413,0.00009292405,0.001421364],"genre_scores_gemma":[0.0009554303,0.002312729,0.000759431,0.01512217,0.9687207,0.00002435492,0.00008772082,0.0001413986,0.01187603],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.03294037,"threshold_uncertainty_score":0.1101965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008890312988525221,"score_gpt":0.2275228686149516,"score_spread":0.2186325556264264,"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."}}