{"id":"W2981629092","doi":"10.4095/297743","title":"Remote sensing activities in Southern Ontario in NRCan/ESS Groundwater Geoscience Program","year":2016,"lang":"en","type":"report","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Groundwater; Earth science; Environmental science; Remote sensing; Geology","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":[0.0005305823,0.0002855696,0.00019167,0.001451633,0.002363817,0.0009733123,0.0004838687,0.0003127005,0.01087712],"category_scores_gemma":[0.000869051,0.0002271815,0.0001972593,0.003957953,0.0003991865,0.0003586964,0.0006901306,0.000216101,0.001302724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02490723,"about_ca_system_score_gemma":0.02926373,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9894674,"about_ca_topic_score_gemma":0.9960625,"domain_scores_codex":[0.999311,0.0000413792,0.00002350675,0.00009622511,0.0003748039,0.0001532384],"domain_scores_gemma":[0.9986273,0.00008344295,0.00007647216,0.00005444457,0.0009409288,0.0002175219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007483472,0.0002464914,0.3924436,0.0008501473,0.00009999411,0.001468635,0.00872158,0.004879253,0.02084217,0.008997651,0.2868923,0.2738098],"study_design_scores_gemma":[0.00004960419,0.00005445378,0.6378302,0.00008175339,0.00002539873,0.00009863974,0.005305307,0.003028661,0.002985515,0.0003923122,0.3501068,0.0000414298],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5487751,0.003146209,0.003075194,0.00692436,0.0002020935,0.0009181009,0.1032539,0.0009903138,0.3327148],"genre_scores_gemma":[0.6151802,0.002687156,0.00853694,0.0006673741,0.00005086213,0.0002826694,0.03725593,0.0001860594,0.3351528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02490723,"threshold_uncertainty_score":0.1807154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0346166188088082,"score_gpt":0.2630554240002335,"score_spread":0.2284388051914253,"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."}}