{"id":"W6945241372","doi":"10.23719/1395247","title":"Great Lakes Proxies Project","year":2018,"lang":"en","type":"dataset","venue":"Environmental Protection Agency (EPA) Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Shapefile; Metadata; Table (database); Population; Field (mathematics); Data source","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001022426,0.001397227,0.0008543716,0.003182509,0.0008797169,0.002077129,0.002678253,0.0009606516,0.05471324],"category_scores_gemma":[0.004810397,0.0005384684,0.0007978969,0.006179754,0.0003298013,0.001489791,0.002626545,0.001218023,0.06265643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001551504,"about_ca_system_score_gemma":0.00239886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06111864,"about_ca_topic_score_gemma":0.1084845,"domain_scores_codex":[0.9987723,0.000261987,0.0001304952,0.0003555339,0.0003321024,0.000147608],"domain_scores_gemma":[0.9981889,0.0003474743,0.0001732764,0.0005248642,0.0005496016,0.0002159081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00002883244,0.000007592582,0.0008886497,0.0001406494,0.00001574872,0.00001452324,0.00002711742,0.0001135532,0.00003640452,0.0005703731,0.9962828,0.001873908],"study_design_scores_gemma":[0.00005998677,0.000006117267,0.004514853,0.0001375052,0.00001375852,0.0000274739,0.0001074386,0.0002950952,0.0001375164,0.001068532,0.9936132,0.00001853624],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002642397,0.00004384336,0.00007401302,0.0001145438,0.00001886192,0.000009221725,0.9976206,0.0003657989,0.001488922],"genre_scores_gemma":[0.0004139995,0.00004160677,0.0002519429,0.00004789837,0.000006299657,0.00006293739,0.9981081,0.00009128894,0.0009759455],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06111864,"threshold_uncertainty_score":0.183034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01733650523964245,"score_gpt":0.2362543660386148,"score_spread":0.2189178607989724,"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."}}