{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001339747,0.0001791595,0.0007288781,0.001057254,0.00008755382,0.0003299487,0.001491495,0.00009402012,0.00000347427],"category_scores_gemma":[0.0002217361,0.0001168817,0.0002026787,0.00241419,0.0002407673,0.005582409,0.0002358171,0.000433685,0.00002163093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000180512,"about_ca_system_score_gemma":0.001748234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.206083e-7,"about_ca_topic_score_gemma":2.201167e-8,"domain_scores_codex":[0.997443,0.00003400382,0.001430362,0.0001551747,0.0007339613,0.0002034739],"domain_scores_gemma":[0.9962463,0.00008025391,0.002225759,0.0003947296,0.0009836372,0.00006935256],"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":[2.648035e-7,0.000005672042,4.345486e-8,0.01336266,0.00001111587,2.286877e-7,0.00003586595,9.851333e-8,0.000002827617,0.1073115,0.0009347465,0.878335],"study_design_scores_gemma":[0.00004542905,0.0001320893,0.000003111786,0.0160305,0.00009401979,0.0001561335,0.00002350698,0.0008078858,0.0000122868,0.0008800681,0.9817029,0.0001121025],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[5.661282e-7,0.9812576,0.01714894,0.0005603309,0.0002503318,0.0002284159,0.000003383087,0.00002844531,0.0005219714],"genre_scores_gemma":[0.0000179138,0.9960881,0.003709886,0.0001380736,0.00001745426,0.000007470846,0.000003474565,0.000003360007,0.00001428717],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9807681,"threshold_uncertainty_score":0.4766299,"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."}}