{"id":"W3184142975","doi":"10.1145/3462757.3466148","title":"Plum2Text","year":2021,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Annotation; Leverage (statistics); Natural language processing; Table (database); Utterance; Natural language; Artificial intelligence; Paraphrase; Task (project management); Information retrieval; Domain (mathematical analysis); Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001394841,0.001926243,0.0007629443,0.004694777,0.001823384,0.002571246,0.003225868,0.001827528,0.06607636],"category_scores_gemma":[0.008882187,0.0006219918,0.001326567,0.004847933,0.0008147625,0.003731825,0.003848619,0.002167146,0.06064582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002460751,"about_ca_system_score_gemma":0.003726344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07872315,"about_ca_topic_score_gemma":0.1177199,"domain_scores_codex":[0.9979348,0.0003573159,0.0001623488,0.0005558256,0.0007260042,0.000263629],"domain_scores_gemma":[0.9963852,0.0008800068,0.0001839818,0.001382777,0.0008860769,0.0002819164],"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":[0.0002484364,0.0000683323,0.001449702,0.0006549128,0.00003167282,0.0003016205,0.0001934304,0.001393763,0.001044616,0.005108484,0.9617425,0.02776252],"study_design_scores_gemma":[0.00007276657,0.00003216764,0.001697884,0.00008076939,0.00001181769,0.0002384368,0.0001558338,0.003841293,0.002146597,0.002909772,0.9887717,0.00004083735],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.004091321,0.0004812938,0.009265244,0.0008972743,0.0003269133,0.0003635418,0.9101689,0.0504851,0.02392048],"genre_scores_gemma":[0.005115936,0.0001225989,0.007822229,0.0002794391,0.00002549886,0.0002631352,0.9790874,0.002207631,0.005076089],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.07872315,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01026153138210599,"score_gpt":0.2613674779868926,"score_spread":0.2511059466047866,"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."}}