{"id":"W6913043941","doi":"10.5683/sp3/z14onx","title":"Radioisotopic and ancillary data (i.e., estimated temperature, precipitation and population in lake watersheds) for 37 Eastern Canadian lakes","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université de Sherbrooke; Université du Québec à Montréal; Queen's University; McGill University","funders":"","keywords":"Precipitation; Population; Hydrology (agriculture); Ancillary data; Acid rain","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007353724,0.001471209,0.0008825959,0.003609263,0.001686008,0.001407022,0.002253053,0.000655592,0.01003047],"category_scores_gemma":[0.003382381,0.0006330935,0.001000663,0.0110945,0.0004428181,0.0005293505,0.0009970759,0.0009236135,0.00470187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01629524,"about_ca_system_score_gemma":0.0328809,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9874028,"about_ca_topic_score_gemma":0.9929129,"domain_scores_codex":[0.9991443,0.00003511871,0.00006564624,0.0001715156,0.0003562429,0.0002271136],"domain_scores_gemma":[0.9969772,0.0001608,0.0002666634,0.0001667735,0.002173387,0.0002551937],"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":[0.0001342878,0.00002282596,0.03604779,0.000949295,0.000235832,0.00008007916,0.000111587,0.001129841,0.000224073,0.001085805,0.9533901,0.006588534],"study_design_scores_gemma":[0.0002328289,0.00001813287,0.2292311,0.0008407693,0.0002607954,0.0001034334,0.0004804871,0.001922184,0.0009412557,0.0008047954,0.7650652,0.00009907818],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00115704,0.0001264496,0.00007211001,0.0000634927,0.000009845564,0.00000921149,0.9977648,0.0000508403,0.0007462183],"genre_scores_gemma":[0.004855321,0.0002137348,0.0004739861,0.00007113742,0.000005906671,0.0000536307,0.9928281,0.00002533893,0.001472841],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01629524,"threshold_uncertainty_score":0.1182308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0420156346055225,"score_gpt":0.2899540914257269,"score_spread":0.2479384568202044,"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."}}