{"id":"W3134942116","doi":"10.1109/icsc50631.2021.00056","title":"Using Conditional Sentence Representation in Pointer Networks for Sentence Ordering","year":2021,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sentence; Computer science; Pointer (user interface); Natural language processing; Artificial intelligence; Representation (politics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00120441,0.001280699,0.000635976,0.00267079,0.000642057,0.001011548,0.001557141,0.001188882,0.005815045],"category_scores_gemma":[0.00643093,0.0004094939,0.001053885,0.002348948,0.0005362401,0.004028722,0.001203926,0.001854743,0.001659554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001322966,"about_ca_system_score_gemma":0.001533692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006419857,"about_ca_topic_score_gemma":0.01171199,"domain_scores_codex":[0.9993994,0.0002059679,0.00004922094,0.0001892469,0.0001029378,0.00005326816],"domain_scores_gemma":[0.9981025,0.001081112,0.0001926086,0.0001803119,0.0003463916,0.00009708088],"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":[0.0008158169,0.0004482199,0.005230949,0.0006766491,0.0002088288,0.0005263732,0.0009756133,0.1915121,0.0222514,0.06926969,0.02864777,0.6794366],"study_design_scores_gemma":[0.00003328424,0.000131445,0.001005859,0.00005727837,0.00009496033,0.000115606,0.00007343054,0.9342404,0.004032638,0.05357989,0.006595544,0.00003956445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03998055,0.001318356,0.9442857,0.0009148276,0.0002401946,0.0002692766,0.003043995,0.005603742,0.004343432],"genre_scores_gemma":[0.6023305,0.001457628,0.3708143,0.0006752504,0.0004250076,0.0009594689,0.01358775,0.0005167996,0.009233346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006419857,"threshold_uncertainty_score":0.01945329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07775070764176942,"score_gpt":0.3255678994740757,"score_spread":0.2478171918323062,"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."}}