{"id":"W294906217","doi":"","title":"Helpful or Unhelpful: A Linear Approach for Ranking Product Reviews","year":2010,"lang":"en","type":"article","venue":"Journal of electronic commerce research","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Helpfulness; Computer science; Product (mathematics); Ranking (information retrieval); Purchasing; The Internet; World Wide Web; Information retrieval; Data science; Marketing; Psychology; Business; 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":[],"consensus_categories":[],"category_scores_codex":[0.0150203,0.0001651972,0.0005275015,0.00060342,0.000360634,0.000257935,0.001995055,0.00007149794,0.00007465874],"category_scores_gemma":[0.001383224,0.0001105914,0.0003551116,0.0014127,0.00007437303,0.0004727555,0.0002559037,0.001833619,0.00001358391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001169557,"about_ca_system_score_gemma":0.0007759015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008768108,"about_ca_topic_score_gemma":0.00002019088,"domain_scores_codex":[0.9964553,0.0004762593,0.0007915885,0.00037138,0.0009581462,0.0009473068],"domain_scores_gemma":[0.9971485,0.0006250851,0.0004035009,0.0007344936,0.0009093113,0.0001790903],"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":[0.0008140557,0.00155802,0.001744591,0.0004197542,0.0006709485,0.00002861309,0.002435421,0.0002962579,0.06040773,0.05125969,0.0854376,0.7949273],"study_design_scores_gemma":[0.001971706,0.001689718,0.0002532835,0.0001497236,0.00005706784,0.0003702377,0.0002065208,0.138817,0.005322668,0.001779607,0.8490009,0.0003815212],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03995654,0.01476152,0.9238814,0.01674408,0.0007849537,0.001846883,0.000001242076,0.00005369842,0.001969711],"genre_scores_gemma":[0.6432298,0.005308752,0.3420166,0.0005000739,0.004043716,0.0001151815,0.00001021759,0.00007503684,0.004700567],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7945458,"threshold_uncertainty_score":0.7966265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1643859954326166,"score_gpt":0.4424971498965129,"score_spread":0.2781111544638963,"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."}}