{"id":"W4232503947","doi":"10.18653/v1/w17-45","title":"Proceedings of the Workshop on New Frontiers in Summarization","year":2017,"lang":"en","type":"paratext","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Nvidia","keywords":"Automatic summarization; Computer science; Data science; Information retrieval","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001506217,0.0001892079,0.000265885,0.0002175872,0.00007157392,0.0002985313,0.003182025,0.000313614,0.00002623031],"category_scores_gemma":[0.0001214111,0.0001189774,0.00006731433,0.0003627757,0.00004978955,0.0004064466,0.0004799997,0.000467943,0.00002983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008353694,"about_ca_system_score_gemma":0.0002044979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000824193,"about_ca_topic_score_gemma":0.00001097203,"domain_scores_codex":[0.9988987,0.00000968493,0.0002238668,0.0003770112,0.0003112142,0.0001794632],"domain_scores_gemma":[0.998913,0.00002077923,0.0004312209,0.0004955036,0.0001049281,0.00003457014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004197606,0.00001410805,0.0001106512,0.00004964164,0.000005282727,3.461748e-7,0.0001919401,0.000002817583,0.00009728181,0.009750291,0.9408447,0.0489287],"study_design_scores_gemma":[0.001787219,0.0002753381,0.001580062,0.01820721,0.00006652968,0.00001645821,0.0001835871,0.01092692,0.2190752,0.211134,0.5333933,0.003354218],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001188497,0.00520682,0.4718559,0.004212891,0.005452749,0.001034109,0.000005014781,0.0002962555,0.5118174],"genre_scores_gemma":[0.003310383,0.0002256583,0.4289149,0.0004056111,0.0002038164,0.00001497055,0.00000672236,0.00002495105,0.566893],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4074515,"threshold_uncertainty_score":0.5913047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01562330408977624,"score_gpt":0.2748374213215636,"score_spread":0.2592141172317873,"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."}}