{"id":"W4404499553","doi":"10.1101/2024.11.18.623821","title":"The problem of unmeasured variables in animal social network analysis: can edge-based multilevel models provide a reliable solution?","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge; University of Calgary","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Computer science; Social network analysis; Econometrics; Multilevel model; Mathematics; Artificial intelligence; Machine learning","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":[0.03501948,0.0009431954,0.002601671,0.001764032,0.001407829,0.003434841,0.00420126,0.003676573,0.003683825],"category_scores_gemma":[0.1715036,0.001163247,0.002257076,0.003281178,0.00309998,0.005829663,0.004016745,0.005313123,0.0006978652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001364927,"about_ca_system_score_gemma":0.00132394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006961795,"about_ca_topic_score_gemma":0.007377553,"domain_scores_codex":[0.9788824,0.01680986,0.0006667005,0.002176469,0.001053861,0.0004107769],"domain_scores_gemma":[0.866672,0.1047635,0.00802045,0.01366155,0.005612315,0.001270232],"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":[0.0003465971,0.0001592729,0.05149087,0.001036643,0.001836933,0.0005607444,0.001947978,0.166201,0.001291151,0.6208163,0.01196518,0.1423475],"study_design_scores_gemma":[0.00003787649,0.00005406858,0.003887737,0.0002173389,0.0001249036,0.0000636225,0.0002067666,0.3405696,0.0003616745,0.6497631,0.004667022,0.00004637167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01723259,0.0006691595,0.9762272,0.004211402,0.0001414608,0.00005058333,0.000409915,0.000153772,0.0009039578],"genre_scores_gemma":[0.4981415,0.001222168,0.4942069,0.00189297,0.0005865394,0.0007661952,0.0009099725,0.0003164606,0.001957257],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03501948,"threshold_uncertainty_score":0.1852029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01636632722055861,"score_gpt":0.2037686020182915,"score_spread":0.1874022747977329,"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."}}