{"id":"W3163735098","doi":"10.48550/arxiv.2105.02923","title":"Hone as You Read: A Practical Type of Interactive Summarization","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Automatic summarization; Computer science; Heuristics; Task (project management); Reading (process); Process (computing); Variety (cybernetics); Metric (unit); Code (set theory); Human–computer interaction; Relevance (law); Artificial intelligence; Programming language","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":[0.003104832,0.001821334,0.00138784,0.00147902,0.001087032,0.002246563,0.00226446,0.002038097,0.01242503],"category_scores_gemma":[0.01615985,0.0004608602,0.0009257257,0.001633544,0.0006523774,0.003897027,0.002675528,0.001721958,0.005566532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005572535,"about_ca_system_score_gemma":0.0006813383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001095817,"about_ca_topic_score_gemma":0.003335658,"domain_scores_codex":[0.9965811,0.001557582,0.0002132566,0.0008829694,0.000588273,0.0001767543],"domain_scores_gemma":[0.9891905,0.006258422,0.0005196017,0.002432859,0.001156921,0.0004418247],"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":[0.001303253,0.0006536982,0.002185022,0.00169443,0.0003357442,0.0004389531,0.0020355,0.03636121,0.04745235,0.009839096,0.07690667,0.820794],"study_design_scores_gemma":[0.000500702,0.002120071,0.004610218,0.0001944459,0.0003256386,0.001221543,0.001680518,0.6507573,0.1093591,0.05469402,0.1741941,0.0003422849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05603703,0.00156641,0.890257,0.001451862,0.0004599259,0.0006939383,0.004224471,0.03290395,0.01240539],"genre_scores_gemma":[0.2340989,0.0004383677,0.7393799,0.0004574152,0.0003235763,0.0005362014,0.009393353,0.002950261,0.01242188],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01242503,"threshold_uncertainty_score":0.0415659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1190926273060999,"score_gpt":0.2408938892290226,"score_spread":0.1218012619229227,"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."}}