{"id":"W2134214966","doi":"10.1109/ccece.1993.332251","title":"Neural networks and document classification","year":2002,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation, Science and Economic Development Canada","funders":"","keywords":"Computer science; Artificial neural network; Relevance (law); Artificial intelligence; Natural language; Backpropagation; Natural language processing; Document classification; Convergence (economics); Machine learning","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":[0.001344152,0.0006370485,0.0005592392,0.004095993,0.0006554858,0.002567182,0.0007822687,0.001965634,0.004002044],"category_scores_gemma":[0.004979722,0.0003002795,0.0005513668,0.005749306,0.001494137,0.003136844,0.0006893313,0.001474984,0.001620465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00181349,"about_ca_system_score_gemma":0.0005327701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004672442,"about_ca_topic_score_gemma":0.005098202,"domain_scores_codex":[0.999136,0.0002426274,0.00007351893,0.0001799846,0.0002808995,0.00008699106],"domain_scores_gemma":[0.9980623,0.001319183,0.0001803772,0.0001176781,0.0002736411,0.00004676788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009825097,0.0001000939,0.003905684,0.0006253666,0.000173366,0.000271284,0.0003226186,0.0629741,0.001682392,0.326666,0.02671357,0.5764674],"study_design_scores_gemma":[0.00002306976,0.00005926593,0.003895067,0.000362871,0.00006990324,0.0005487205,0.0001679309,0.2981888,0.003252607,0.5679659,0.1253983,0.00006772191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02607239,0.1097872,0.7502683,0.01800643,0.002687835,0.0001662243,0.001191995,0.00111407,0.09070554],"genre_scores_gemma":[0.5096835,0.09519813,0.3104646,0.003612908,0.006392844,0.0004183042,0.002838067,0.0002687795,0.07112286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004672442,"threshold_uncertainty_score":0.01338816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02799713016883222,"score_gpt":0.2355946331855666,"score_spread":0.2075975030167344,"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."}}