{"id":"W2994747004","doi":"10.1016/j.elerap.2019.100917","title":"A neural graph embedding approach for selecting review sentences","year":2019,"lang":"en","type":"article","venue":"Electronic Commerce Research and Applications","topic":"Topic Modeling","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Embedding; Artificial intelligence; Graph; Natural language processing; Machine learning; Theoretical computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001284125,0.0000930401,0.0001528169,0.0001049223,0.0004107156,0.0001265767,0.0007094271,0.00003085415,0.000004679335],"category_scores_gemma":[0.000026944,0.00008529879,0.00004704212,0.0007729738,0.00004161431,0.0001882021,0.0002116362,0.0004024668,0.000007593447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000562794,"about_ca_system_score_gemma":0.0001059798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002219085,"about_ca_topic_score_gemma":0.000003836272,"domain_scores_codex":[0.9982875,0.00008835465,0.0001772653,0.0004853712,0.0002659984,0.0006954867],"domain_scores_gemma":[0.9988331,0.0003459735,0.0000418785,0.0005337242,0.000149501,0.00009584884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006336761,0.0001383211,0.0006714444,0.0008786417,0.00003285328,1.222544e-7,0.0001830409,0.000259784,0.001946434,0.6468613,0.002017924,0.3470038],"study_design_scores_gemma":[0.0004739621,0.0003356744,0.0001054478,0.0001960197,0.000008321824,0.00004942102,0.0002281174,0.817972,0.0001942872,0.03691382,0.1431742,0.0003487371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002857004,0.02091429,0.9691833,0.00370192,0.000009934093,0.001801613,0.000001160851,0.00008365054,0.001447099],"genre_scores_gemma":[0.9214361,0.01249404,0.06141904,0.0007184283,0.0001674472,0.002962336,0.00002472306,0.00002283329,0.0007550155],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9185791,"threshold_uncertainty_score":0.3478384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06821664792207113,"score_gpt":0.3889785058434018,"score_spread":0.3207618579213307,"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."}}