{"id":"W113882479","doi":"10.1007/978-3-642-21043-3_16","title":"Consolidation Using Context-Sensitive Multiple Task Learning","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; Consolidation (business); Artificial intelligence; Transfer of learning; Task (project management); Knowledge transfer; Context (archaeology); Machine learning; Knowledge management; Engineering","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":[0.002435384,0.001606112,0.002541683,0.001031226,0.0007151963,0.00196807,0.004140156,0.001643849,0.005774394],"category_scores_gemma":[0.00755284,0.00104057,0.001150077,0.001732777,0.0008096444,0.004764176,0.004091484,0.003928682,0.002525575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005712003,"about_ca_system_score_gemma":0.001263594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001886349,"about_ca_topic_score_gemma":0.002104013,"domain_scores_codex":[0.9988039,0.000294371,0.00009545533,0.0004815058,0.0001889118,0.0001357698],"domain_scores_gemma":[0.9950788,0.002389035,0.0002366816,0.001231034,0.0007452219,0.0003193177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005255297,0.000584199,0.0008067164,0.0002095641,0.0002099696,0.0001100465,0.0001377158,0.05692994,0.0320148,0.006075955,0.006120001,0.8962757],"study_design_scores_gemma":[0.00004641725,0.000167063,0.000439051,0.00001954404,0.00005978292,0.00008125198,0.00002905208,0.9588152,0.01520948,0.02348804,0.001608967,0.00003610831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01737846,0.0007060019,0.9766191,0.000148891,0.0002763443,0.0001261782,0.0001177818,0.003013754,0.001613493],"genre_scores_gemma":[0.587276,0.0007328697,0.4019476,0.000433939,0.0003490078,0.0004754507,0.001226459,0.00074505,0.006813644],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005774394,"threshold_uncertainty_score":0.01931733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03743050568410767,"score_gpt":0.2536641098639091,"score_spread":0.2162336041798015,"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."}}