{"id":"W2959013365","doi":"10.18280/isi.240119","title":"Sentiment Analysis from Movie Reviews Using LSTMs","year":2019,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sentiment analysis; Computer science; Natural language processing; Artificial intelligence; Information retrieval","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000462159,0.0007636451,0.000448851,0.0007839096,0.0001615919,0.0004253135,0.0003481965,0.0004696865,0.001738813],"category_scores_gemma":[0.002001449,0.0002202245,0.0005251657,0.0006633163,0.000113353,0.0004927365,0.000267739,0.0006068962,0.001198606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003699224,"about_ca_system_score_gemma":0.0002896763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003279543,"about_ca_topic_score_gemma":0.004132106,"domain_scores_codex":[0.9997496,0.00005260427,0.00002077437,0.00005430486,0.00008355785,0.00003919322],"domain_scores_gemma":[0.9994581,0.0001427138,0.00008062179,0.00002492521,0.0002724509,0.00002111014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009492338,0.0002844979,0.01015845,0.000434685,0.000318374,0.0008569522,0.0003342914,0.1141975,0.1298861,0.001553204,0.01851663,0.72251],"study_design_scores_gemma":[0.00001630236,0.00012343,0.005575288,0.00002067242,0.00003656118,0.00007774559,0.00006445594,0.9793469,0.01103648,0.001097002,0.002587592,0.00001749343],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5011044,0.003185158,0.4748262,0.001211916,0.0009166155,0.0002514141,0.003349507,0.005262322,0.009892534],"genre_scores_gemma":[0.9136158,0.0007863674,0.07570034,0.0002064622,0.000322181,0.0001219594,0.003491536,0.0001361255,0.00561922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003279543,"threshold_uncertainty_score":0.006520867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04026820360881078,"score_gpt":0.2761655489065912,"score_spread":0.2358973452977804,"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."}}