{"id":"W3048896201","doi":"10.1007/s40471-020-00242-5","title":"Trajectory Modeling with Latent Groups: Potentials and Pitfalls","year":2020,"lang":"en","type":"article","venue":"Current Epidemiology Reports","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Sciences Centre; Université Laval; Foothills Medical Centre; University of Calgary","funders":"Alberta Children's Hospital Research Institute; Alberta Innovates - Health Solutions","keywords":"Trajectory; Data science; Latent class model; Computer science; Field (mathematics); Psychology; Machine learning; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1006995,0.001984481,0.004653743,0.002938029,0.00199224,0.007788351,0.008213593,0.004408642,0.003021218],"category_scores_gemma":[0.2400259,0.002240045,0.002673208,0.005382844,0.007517298,0.01312714,0.007423129,0.0119429,0.001059827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00270793,"about_ca_system_score_gemma":0.004603723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02515551,"about_ca_topic_score_gemma":0.02298996,"domain_scores_codex":[0.9444035,0.04662986,0.001521404,0.003905063,0.003086581,0.0004536929],"domain_scores_gemma":[0.5528417,0.4232467,0.004459338,0.01343871,0.004476121,0.001537521],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005753275,0.0002919581,0.04275771,0.001272113,0.001293226,0.0004857559,0.002477465,0.1957716,0.0002915454,0.533478,0.01153737,0.209768],"study_design_scores_gemma":[0.00005619382,0.00004550883,0.001100018,0.0002280526,0.00006627087,0.0001465946,0.0003281552,0.366926,0.0001312548,0.6273779,0.003536189,0.00005791693],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008517493,0.004466408,0.97131,0.01275547,0.0002625998,0.00022419,0.0005448214,0.0004110746,0.001507994],"genre_scores_gemma":[0.3498687,0.005726312,0.6355526,0.002984943,0.001507097,0.001187291,0.001012206,0.0002924385,0.001868519],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8993006,"threshold_uncertainty_score":0.5325559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1049471048114064,"score_gpt":0.3349753570556964,"score_spread":0.23002825224429,"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."}}