{"id":"W344868967","doi":"","title":"Agriculture Canada Central Saskatchewan Vector Soils Data","year":2000,"lang":"en","type":"article","venue":"NASA Technical Reports Server (NASA)","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Soil water; Data set; Soil survey; Polygon (computer graphics); Agriculture; Soil map; Geology; Soil science; Database; Geography; Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003787988,0.0003528998,0.0004031199,0.00003613883,0.0002645779,0.0002759392,0.002698651,0.0002610057,0.0003979992],"category_scores_gemma":[0.0001146486,0.0002675806,0.0001009067,0.0005629242,0.00005845927,0.001152396,0.001476412,0.0005600142,0.00002028932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002549664,"about_ca_system_score_gemma":0.001272087,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1643422,"about_ca_topic_score_gemma":0.2414461,"domain_scores_codex":[0.995777,0.00006927645,0.0007385758,0.001354388,0.001230848,0.0008299034],"domain_scores_gemma":[0.995006,0.00007774757,0.0002468771,0.00403343,0.00011,0.0005259403],"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":[0.00002460465,0.0004172846,0.002730994,0.0000483449,0.00006327525,0.005934172,0.0001111654,0.0002467102,0.002231242,0.0004413047,0.8408521,0.1468988],"study_design_scores_gemma":[0.0004165704,0.000103552,0.1239935,0.000148292,0.00003729747,0.001799013,0.00003832334,0.004847936,0.001617395,0.0008670384,0.8651084,0.001022638],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8744345,0.00387485,0.06681477,0.01445935,0.01028026,0.003434639,0.001043367,0.005453839,0.02020443],"genre_scores_gemma":[0.9740274,0.00005320569,0.02123754,0.001162202,0.000586664,0.00002267685,0.0005651296,0.00002553216,0.00231963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1458762,"threshold_uncertainty_score":0.9999776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01370595508256043,"score_gpt":0.2300219447644981,"score_spread":0.2163159896819376,"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."}}