{"id":"W204776251","doi":"10.1007/978-3-642-21043-3_18","title":"Compact Features for Sentiment Analysis","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Artificial intelligence","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":[0.0005385728,0.000920961,0.0008769404,0.001587692,0.0004568547,0.001148177,0.0006849063,0.000555191,0.01115261],"category_scores_gemma":[0.002865321,0.0003831367,0.0006603395,0.002122424,0.0002308208,0.002139384,0.001128832,0.001055292,0.006254265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002829196,"about_ca_system_score_gemma":0.0003173366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005773811,"about_ca_topic_score_gemma":0.0008435899,"domain_scores_codex":[0.9995368,0.00007852975,0.0000506611,0.0001052319,0.000178567,0.00005020419],"domain_scores_gemma":[0.9991044,0.0003269064,0.00008915468,0.0002113779,0.0002344531,0.0000336685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002879231,0.00009108027,0.0004507878,0.0002049791,0.00005094194,0.0001026535,0.00005656468,0.005133556,0.03576137,0.01247855,0.0314307,0.9139509],"study_design_scores_gemma":[0.0001412117,0.0004162976,0.004796448,0.0001488904,0.0001757438,0.0007220194,0.0001436292,0.6927676,0.05964617,0.136653,0.1042923,0.0000966618],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0145549,0.00120518,0.969106,0.000227215,0.00039847,0.0001451278,0.002856699,0.007099667,0.004406676],"genre_scores_gemma":[0.2327271,0.001385749,0.7323949,0.0002363609,0.0007324608,0.0007644892,0.01454111,0.001435271,0.01578258],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01115261,"threshold_uncertainty_score":0.03730923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02912507084799413,"score_gpt":0.276080730006287,"score_spread":0.2469556591582929,"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."}}