{"id":"W6923183060","doi":"10.1371/journal.pone.0212637.t002","title":"Negative binomial generalized estimating equation models testing for the influence of the number of <i>I</i>. <i>scapularis</i> tick submissions on the occurrence of human Lyme disease cases; adult and nymphal <i>I</i>. <i>scapularis</i> submissions (Model 1) and nymphal <i>I</i>. <i>scapularis</i> submissions (Model 2) detected by the passive tick surveillance program in Ontario and Manitoba.","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"Education Methods and Technologies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lyme disease; Tick; Negative binomial distribution; Borrelia burgdorferi; Tick-borne disease; Generalized estimating equation; Binomial distribution; Binomial (polynomial)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","research_integrity"],"category_scores_codex":[0.006606288,0.005955472,0.006303896,0.002125341,0.009527508,0.002273369,0.009621792,0.004895998,0.002385876],"category_scores_gemma":[0.04182544,0.004633925,0.002391729,0.006300341,0.005796591,0.00326591,0.004848447,0.004388917,0.0001476951],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002933098,"about_ca_system_score_gemma":0.009619044,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001739532,"about_ca_topic_score_gemma":0.06500848,"domain_scores_codex":[0.9652279,0.006402358,0.007965792,0.007076496,0.007103828,0.006223646],"domain_scores_gemma":[0.9546936,0.01678805,0.01017479,0.008460468,0.006885352,0.00299778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003847859,0.008322964,0.003139237,0.005351606,0.003496101,0.000373998,0.01823861,0.04672782,0.2279582,0.04297259,0.6192428,0.02032815],"study_design_scores_gemma":[0.0230115,0.00436504,0.04395176,0.02482298,0.008652601,0.0006515642,0.002478096,0.3667036,0.003750053,0.03244208,0.4696558,0.0195149],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3460242,0.01048766,0.001345761,0.002817666,0.001949511,0.02059381,0.6138482,0.001265912,0.001667273],"genre_scores_gemma":[0.7577651,0.003121446,0.01416873,0.0007698569,0.00138541,0.01100517,0.2075981,0.001116236,0.003070005],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4117409,"threshold_uncertainty_score":0.9987624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07465273416017229,"score_gpt":0.3304200772145407,"score_spread":0.2557673430543684,"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."}}