{"id":"W1588719833","doi":"10.1007/978-3-540-71496-5_37","title":"Ad Hoc Retrieval of Documents with Topical Opinion","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Information retrieval; Computer science; Query expansion; Term (time); Document retrieval; Post hoc; Domain (mathematical analysis); Web query classification; Search engine; Web search query; World Wide Web; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000808242,0.0003617814,0.0005274362,0.0008215668,0.0001206686,0.0002358878,0.002095706,0.0002274544,0.00005141187],"category_scores_gemma":[0.00002767123,0.0002872361,0.0001369359,0.0006948973,0.0004601934,0.0004313677,0.0007755059,0.0004650984,0.0000185499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001483786,"about_ca_system_score_gemma":0.0002845923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005328782,"about_ca_topic_score_gemma":0.00001480093,"domain_scores_codex":[0.9964599,0.00002209377,0.0005619236,0.001091113,0.001392325,0.000472671],"domain_scores_gemma":[0.9980034,0.0002474884,0.0003823347,0.001018124,0.0002087261,0.0001399247],"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":[0.00006742703,0.00007142047,0.0005800216,0.00006255871,0.00006735732,0.00007547185,0.000945997,0.005012311,0.0001636254,0.02951552,0.00004106874,0.9633972],"study_design_scores_gemma":[0.004306177,0.004733637,0.004966972,0.004759155,0.0001104868,0.0002751114,0.000002994798,0.8052611,0.02357835,0.105081,0.04231529,0.004609696],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002459447,0.000862368,0.9944067,0.0003267069,0.001140995,0.0001830747,0.000001218733,0.00004772407,0.002785274],"genre_scores_gemma":[0.09629074,0.0003496476,0.900764,0.0009697806,0.0006385388,0.000002054517,0.00001469789,0.00004116366,0.0009293327],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9587875,"threshold_uncertainty_score":0.999958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02581938624542893,"score_gpt":0.2864166207459558,"score_spread":0.2605972345005268,"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."}}