{"id":"W4396964204","doi":"10.23977/jeis.2024.090205","title":"A Comprehensive Review of Text Classification Algorithms","year":2024,"lang":"en","type":"review","venue":"Journal of Electronics and Information Science","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Algorithm; Artificial intelligence","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":[0.001476919,0.001019659,0.001338048,0.006063715,0.0005618278,0.001671197,0.001377843,0.00114737,0.009049908],"category_scores_gemma":[0.005181295,0.0003328171,0.0009498979,0.006285162,0.0004594441,0.003690582,0.0006306094,0.001251955,0.008539364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007251899,"about_ca_system_score_gemma":0.001814166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001579944,"about_ca_topic_score_gemma":0.001909088,"domain_scores_codex":[0.9990101,0.0001649928,0.0001495678,0.0001720136,0.0004472561,0.00005599749],"domain_scores_gemma":[0.9969249,0.00171309,0.0001796017,0.0001015047,0.001003236,0.00007758491],"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":[0.00003061043,0.00004440462,0.0002265019,0.005967132,0.00004103519,0.00003322535,0.00003718214,0.0003163682,0.000576055,0.002684825,0.05429448,0.9357483],"study_design_scores_gemma":[0.00001265488,0.00008265377,0.001372064,0.004661856,0.0001230992,0.0004004533,0.00007830354,0.001149619,0.0009516381,0.005010901,0.9861186,0.00003816683],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000760444,0.9744241,0.01103453,0.002093877,0.00186496,0.0001099349,0.0005296313,0.0003552146,0.008827382],"genre_scores_gemma":[0.004414609,0.9652685,0.01679249,0.001533611,0.002893166,0.0001644655,0.001565189,0.00009441865,0.007273665],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009049908,"threshold_uncertainty_score":0.03027499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04890500620325289,"score_gpt":0.3591782347321874,"score_spread":0.3102732285289345,"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."}}