{"id":"W3215511319","doi":"10.1016/j.istruc.2021.11.018","title":"The twenty-first century of structural engineering research: A topic modeling approach","year":2021,"lang":"en","type":"article","venue":"Structures","topic":"BIM and Construction Integration","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Latent Dirichlet allocation; Topic model; Similarity (geometry); Theme (computing); Computer science; Data science; Political science; Library science; Information retrieval; World Wide Web; Artificial intelligence","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.004932075,0.0009439456,0.001134122,0.006966338,0.003111044,0.01164557,0.00210353,0.002971123,0.008455928],"category_scores_gemma":[0.004950938,0.0006651734,0.0007640808,0.00678432,0.01494805,0.01321549,0.003147656,0.003311652,0.001014308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007546223,"about_ca_system_score_gemma":0.005380156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005789752,"about_ca_topic_score_gemma":0.006339627,"domain_scores_codex":[0.9975277,0.001484734,0.0001096474,0.0003193531,0.0004323031,0.000126419],"domain_scores_gemma":[0.9960153,0.00280669,0.0001708659,0.0003163096,0.0004321556,0.0002586462],"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":[0.000008891046,0.00001808378,0.0001877737,0.0001078064,0.000008366021,0.00005170568,0.002984637,0.0009165662,0.00008007423,0.9823682,0.002317661,0.01095017],"study_design_scores_gemma":[0.000009181638,0.00002516634,0.000478318,0.0003552641,0.00001628434,0.0001513741,0.004548053,0.004019212,0.0001853339,0.7351391,0.2550547,0.00001811127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03381923,0.1342624,0.4057062,0.08101937,0.003917146,0.000185069,0.0006712566,0.0004713471,0.339948],"genre_scores_gemma":[0.6585346,0.1059479,0.1436035,0.008303526,0.004475915,0.0006686157,0.0005330761,0.0006319258,0.07730088],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9930336,"threshold_uncertainty_score":0.05475187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02625650762190919,"score_gpt":0.2509651179561673,"score_spread":0.2247086103342581,"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."}}