{"id":"W94318738","doi":"","title":"Synonym-Based Expansion and Boosting-Based Re-Ranking: A Two-phase Approach for Genomic Information Retrieval.","year":2005,"lang":"en","type":"article","venue":"Text REtrieval Conference","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Boosting (machine learning); WordNet; Information retrieval; Artificial intelligence; Ranking (information retrieval); Machine learning","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":[0.005392751,0.00117083,0.001808679,0.007026738,0.001040141,0.001456901,0.001894101,0.001159405,0.002986779],"category_scores_gemma":[0.009490428,0.0005584182,0.001177884,0.00516084,0.0005774494,0.002687557,0.001772463,0.001182711,0.004304155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006187105,"about_ca_system_score_gemma":0.001305351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001937428,"about_ca_topic_score_gemma":0.004664458,"domain_scores_codex":[0.9958961,0.001704541,0.0002527652,0.0006063238,0.001316864,0.0002234168],"domain_scores_gemma":[0.995863,0.00128404,0.0003141618,0.000865693,0.001512692,0.0001605117],"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":[0.0003744726,0.0004446272,0.00270353,0.000447616,0.0002130195,0.0002111561,0.0004088,0.009178377,0.05300895,0.005177511,0.02060935,0.9072226],"study_design_scores_gemma":[0.0002983659,0.001238483,0.0167299,0.0001580266,0.0005721902,0.002293222,0.0006190575,0.6996439,0.117108,0.04860067,0.1123248,0.0004135777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02056872,0.001985152,0.9645828,0.0003393569,0.0002523824,0.0007570464,0.0006477695,0.006997914,0.003868911],"genre_scores_gemma":[0.1104763,0.0006553431,0.8806005,0.0003231873,0.0002267184,0.0004263466,0.002515841,0.0003501831,0.004425517],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007026738,"threshold_uncertainty_score":0.02851993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02894459750801155,"score_gpt":0.2989211651388505,"score_spread":0.269976567630839,"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."}}