{"id":"W2027473514","doi":"10.7901/2169-3358-2003-1-245","title":"Integrating Data, Resources, and Capabilities in the Great Lakes: Impacting Federal, State, Tribal, Local, and Private Partnerships through the Area Committee","year":2003,"lang":"en","type":"article","venue":"International Oil Spill Conference Proceedings","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Watershed; Recreation; Superfund; Environmental planning; Business; Remedial action; Environmental protection; Environmental science; Environmental resource management; Hazardous waste; Ecology; Engineering; Environmental remediation; Waste management; Contamination","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":[],"consensus_categories":[],"category_scores_codex":[0.0009024739,0.0001713541,0.0001495308,0.0000265434,0.0004367386,0.0003218829,0.0005532082,0.00004181263,0.0001328473],"category_scores_gemma":[0.0006315256,0.0001024145,0.00001502734,0.0001152419,0.0008366873,0.0006571487,0.0004372857,0.0002782289,0.000006376248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006610221,"about_ca_system_score_gemma":0.000008871775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004649704,"about_ca_topic_score_gemma":0.003701474,"domain_scores_codex":[0.9988224,0.00004747824,0.0002464723,0.0003696471,0.000260142,0.0002538509],"domain_scores_gemma":[0.9993999,0.0002746206,0.0001327361,0.0001331656,0.00003196503,0.00002760189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000045221,0.00005636995,0.9196057,0.00004340666,0.00006686637,0.000006956705,0.03265907,0.00001531312,0.00005801456,0.02626848,0.01728046,0.003894159],"study_design_scores_gemma":[0.001769228,0.0003143946,0.3687935,0.0003077096,0.00006595545,0.0001290227,0.2182258,0.006202804,0.0001299382,0.078206,0.3250401,0.0008155284],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9070808,0.00007008637,0.0001482131,0.008581786,0.00006059192,0.0001534034,0.00001092514,0.00002255687,0.08387166],"genre_scores_gemma":[0.9971009,0.0003262557,0.0002593711,0.001625734,0.00001391477,0.00004778372,0.000006729872,0.000006824317,0.0006124668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5508121,"threshold_uncertainty_score":0.4176343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05673507768162668,"score_gpt":0.2702771661415049,"score_spread":0.2135420884598783,"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."}}