{"id":"W206612899","doi":"10.1023/a:1021396101299","title":"Bi-National Assessment of the Great Lakes: SOLEC Partnerships","year":2003,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Water Resources and Governance","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"Health Canada; Natural Resources Canada; U.S. Geological Survey","keywords":"Agency (philosophy); Environmental resource management; Government (linguistics); Corporate governance; Ecosystem services; Ecosystem health; Natural resource; Environmental planning; Business; Environmental quality; Ecosystem; Quality (philosophy); Resource (disambiguation); Baseline (sea); Geography; Environmental science; Ecology; Computer science; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004152926,0.00009321512,0.00009785908,0.00001428045,0.00041137,0.00004462939,0.0001280148,0.00004160952,0.00007070995],"category_scores_gemma":[0.00001037156,0.00007011196,0.0000525685,0.00005573181,0.0002116325,0.00009030379,0.00004806688,0.0001288969,0.000001861415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002406076,"about_ca_system_score_gemma":0.00007037842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009463045,"about_ca_topic_score_gemma":0.00001580618,"domain_scores_codex":[0.9986387,0.0001703326,0.0001446181,0.0001705956,0.0006801802,0.0001955317],"domain_scores_gemma":[0.9996587,0.00005178797,0.0001042806,0.0001097209,0.000005435184,0.00007006043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001068032,0.00008780739,0.9851184,0.000006155718,0.00001953883,8.962654e-7,0.0009287552,0.00006370662,0.001504404,0.01092999,0.00007488603,0.001264317],"study_design_scores_gemma":[0.0002724924,0.00003537087,0.8389133,0.0000410159,0.00001383104,0.000001010146,0.002923259,0.0000246113,0.001977768,0.0005476685,0.1551247,0.0001249543],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9718416,0.0001622899,0.00004078925,0.0005220055,0.0003631177,0.0001451704,0.00001154564,0.00001055172,0.02690295],"genre_scores_gemma":[0.996363,0.0002020708,0.0007542024,0.00001935129,0.0001458002,0.00001827541,0.000001022613,0.000007078606,0.002489143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1550498,"threshold_uncertainty_score":0.3163967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04482089318799552,"score_gpt":0.3191083095384977,"score_spread":0.2742874163505022,"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."}}