{"id":"W6976965046","doi":"10.60692/kwcnw-nrs71","title":"Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval","year":2021,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Semantics (computer science); Generative grammar; Computational linguistics; Joint (building); Natural language; Natural (archaeology); Computational semantics; Natural language generation","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":[0.001806205,0.0008726423,0.001932129,0.002779565,0.0007689467,0.001586507,0.00232926,0.001634928,0.002248761],"category_scores_gemma":[0.005976652,0.0009700301,0.002053109,0.002572875,0.0008972578,0.003910752,0.00171666,0.001642289,0.001217388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001425074,"about_ca_system_score_gemma":0.001130361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01695735,"about_ca_topic_score_gemma":0.02979553,"domain_scores_codex":[0.999216,0.0003729997,0.00004798598,0.0001801227,0.0001146845,0.00006820301],"domain_scores_gemma":[0.9972154,0.002106174,0.0001433355,0.0002314607,0.0002060231,0.00009759837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004846181,0.0002620464,0.003829245,0.0002572566,0.0003594242,0.0001886999,0.0003814707,0.7272924,0.002511928,0.06984085,0.009568892,0.1850232],"study_design_scores_gemma":[0.00001703938,0.00001709911,0.0001368857,0.000005490362,0.00002802744,0.00002138043,0.00001248096,0.9687205,0.0001534589,0.03038629,0.0004926002,0.000008883718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0309439,0.002733198,0.9616676,0.0006401729,0.0001011073,0.0001012508,0.0004953208,0.001661532,0.001655839],"genre_scores_gemma":[0.7590947,0.002086916,0.22902,0.0004248831,0.000378236,0.0003763448,0.00216659,0.0007810497,0.005671186],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01695735,"threshold_uncertainty_score":0.03371727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0268192088940337,"score_gpt":0.2120414345744637,"score_spread":0.18522222568043,"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."}}