{"id":"W2122560301","doi":"10.5539/cis.v6n4p125","title":"Abstract Sentence Classification for Scientific Papers Based on Transductive SVM","year":2013,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Ministry of Education, India","keywords":"Computer science; Sentence; Support vector machine; Artificial intelligence; Natural language processing; Machine learning; Pattern recognition (psychology)","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005379471,0.0001186341,0.00008999706,0.0005067239,0.0006345147,0.001981133,0.0009506703,0.00004386198,0.00001428431],"category_scores_gemma":[0.0000701708,0.00009740276,0.00003645386,0.0009269852,0.000582738,0.01114968,0.00007934648,0.00007737244,0.0001049524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005363315,"about_ca_system_score_gemma":0.0001341833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002527764,"about_ca_topic_score_gemma":1.389175e-7,"domain_scores_codex":[0.998645,0.000008354658,0.0002854264,0.0003547079,0.0004459811,0.0002605195],"domain_scores_gemma":[0.9987175,0.0001029813,0.0001515179,0.000503949,0.0004264015,0.00009765703],"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":[0.000004437187,0.0000387286,0.0001795518,0.00002674668,0.000001879537,5.027239e-8,0.000881227,0.000361522,0.005086258,0.2461176,0.0015054,0.7457966],"study_design_scores_gemma":[0.0003299809,0.0001036241,0.104206,0.00001995659,0.000001266741,0.000001416398,0.0001896566,0.874255,0.004375669,0.002247624,0.01408528,0.0001845052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0191357,0.00000563275,0.9701456,0.004755778,0.0006029787,0.0006003489,0.000004008441,0.0003203764,0.004429555],"genre_scores_gemma":[0.9532086,0.000004766665,0.04576999,0.0008654001,0.00001613903,0.000102343,0.000008145637,0.000001939617,0.00002270954],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9340729,"threshold_uncertainty_score":0.9990549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02469599365470214,"score_gpt":0.2510553728594687,"score_spread":0.2263593792047666,"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."}}