{"id":"W3132661408","doi":"10.4095/327585","title":"Groundwater Information Network: GIN","year":2021,"lang":"en","type":"report","venue":"","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Groundwater; Water resource management; Hydrology (agriculture); Environmental science; Geology; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001771382,0.001351216,0.001141047,0.004965783,0.0009869359,0.004566192,0.002375374,0.001637185,0.1888976],"category_scores_gemma":[0.01061111,0.0006358012,0.0006252647,0.01251165,0.0003887352,0.004833454,0.003683656,0.001761578,0.2103817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002047548,"about_ca_system_score_gemma":0.005245771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02514974,"about_ca_topic_score_gemma":0.020665,"domain_scores_codex":[0.9985322,0.0002167723,0.000132136,0.0003438919,0.000582964,0.0001920842],"domain_scores_gemma":[0.9962615,0.0004644457,0.0002225099,0.000979119,0.001640748,0.000431647],"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":[0.00004310725,0.000008037441,0.0002989698,0.0001427789,0.000008178818,0.00001233398,0.00002257846,0.0002745294,0.0001439598,0.005974933,0.9799418,0.01312891],"study_design_scores_gemma":[0.00002433748,0.000004463224,0.0004466876,0.00008636956,0.000007489079,0.00001978857,0.00003603043,0.0009112653,0.0002420611,0.007976179,0.9902311,0.00001430214],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003955034,0.0003710866,0.005067535,0.001504292,0.0002280972,0.0001073967,0.9003481,0.0173821,0.07459585],"genre_scores_gemma":[0.003865842,0.0006744404,0.008195428,0.0006329232,0.0000871829,0.0002100995,0.9596416,0.004911462,0.02178107],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1888976,"threshold_uncertainty_score":0.6319254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03370652664334479,"score_gpt":0.3099191052967995,"score_spread":0.2762125786534547,"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."}}