{"id":"W2996035247","doi":"","title":"A NEW METHOD FOR PRIORITIZING CATCHMENTS FOR TERRESTRIAL LIMING IN NOVA SCOTIA","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Water Resources and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Nova scotia; Nova (rocket); Environmental science; Forestry; Geography; Archaeology; Engineering","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":[0.0007908646,0.0005069369,0.0003970231,0.003281353,0.0009238978,0.001462464,0.0006048008,0.0003466329,0.002352839],"category_scores_gemma":[0.003026111,0.0002651294,0.0003310081,0.002054429,0.0001986979,0.0003419749,0.000733453,0.0003404005,0.0002658541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003318347,"about_ca_system_score_gemma":0.005541983,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6914177,"about_ca_topic_score_gemma":0.8666863,"domain_scores_codex":[0.9995409,0.00007162796,0.00003868021,0.0001073351,0.0001539979,0.00008752521],"domain_scores_gemma":[0.9987184,0.0003425218,0.0001099661,0.00004593567,0.0006687155,0.0001143929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005553244,0.0003626866,0.4370182,0.0003674447,0.0003996711,0.0008944191,0.001564154,0.08773681,0.01664589,0.003321057,0.02426416,0.4268702],"study_design_scores_gemma":[0.0001729869,0.0000894051,0.2725455,0.00009507508,0.0001580622,0.0002417407,0.002112124,0.7040212,0.004268817,0.002095657,0.0141156,0.00008382364],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8042006,0.0006971038,0.153494,0.0009245911,0.0001589809,0.001157662,0.01089099,0.002038195,0.02643783],"genre_scores_gemma":[0.7773232,0.0001942977,0.2109109,0.00009184198,0.00002610265,0.0002573677,0.002683574,0.0001017413,0.008411077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3085823,"threshold_uncertainty_score":0.6207992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0422122192863117,"score_gpt":0.3538772903158092,"score_spread":0.3116650710294975,"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."}}