{"id":"W6968514267","doi":"10.5281/zenodo.15350060","title":"Lakes, Rivers and Glaciers in Canada - CanVec Series - Hydrographic Features","year":2019,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Parasites and Host Interactions","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydrography; Hydrographic survey; Geospatial analysis; Glacier; Snow; Series (stratigraphy)","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001496756,0.0001933359,0.0002410256,0.0003098856,0.0008912948,0.0001771705,0.0005971384,0.0001723671,0.01036794],"category_scores_gemma":[0.0001481253,0.0002015278,0.0000372737,0.0002854322,0.0002045062,0.0001402263,0.000528388,0.0007201376,0.002511167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002980334,"about_ca_system_score_gemma":0.00004275761,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.29488,"about_ca_topic_score_gemma":0.1427163,"domain_scores_codex":[0.9987101,0.0002652264,0.0001963803,0.0003852518,0.00007447847,0.0003685433],"domain_scores_gemma":[0.9993045,0.00003215848,0.0001132601,0.0003790568,0.0001170824,0.00005390258],"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":[0.00007487091,0.00003001508,0.00001863778,0.0000539652,0.0001045385,0.00002504701,0.000102544,0.000009253966,0.0005342615,0.00005125909,0.9970592,0.001936368],"study_design_scores_gemma":[0.0003799209,0.0001069527,0.001449923,0.00004799804,0.00002932288,0.0003727131,0.000321481,9.399769e-7,0.00005742671,0.000008076003,0.9970244,0.0002008736],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007371109,0.0009694903,0.000001080052,0.0003397048,0.0004997803,0.0003328492,0.9869959,0.00007243268,0.003417599],"genre_scores_gemma":[0.01105989,0.0009782468,0.000003493351,0.0001427512,0.00002660451,5.628733e-8,0.9854808,0.0002881347,0.002020045],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1521637,"threshold_uncertainty_score":0.9982655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01456958730616619,"score_gpt":0.2300137541050444,"score_spread":0.2154441667988782,"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."}}