{"id":"W6939612068","doi":"10.6084/m9.figshare.16447251.v1","title":"Subglacial hydrology within the Amery Ice Shelf catchment","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydrology (agriculture); Ice shelf; Shelf ice; Heat flux; Bathymetry; Stereographic projection; Drainage basin; Ice sheet; Arctic","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":[0.0004294423,0.0002072439,0.0002316632,0.0009864743,0.0002200824,0.0007230737,0.0004801499,0.0003003812,0.009606766],"category_scores_gemma":[0.0008960463,0.0001851625,0.0002989694,0.002670739,0.0002110774,0.000481745,0.0006194878,0.0003556296,0.002563002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00092553,"about_ca_system_score_gemma":0.001540112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1303944,"about_ca_topic_score_gemma":0.1674571,"domain_scores_codex":[0.9998083,0.00001297265,0.00001543044,0.00004925606,0.00007843767,0.00003571704],"domain_scores_gemma":[0.9991363,0.000118122,0.0001250124,0.0001251287,0.0003703185,0.000125137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007954962,0.0001967639,0.4929639,0.0007597377,0.0003454074,0.0003943966,0.001715425,0.01666933,0.005541859,0.003014323,0.4169457,0.06065769],"study_design_scores_gemma":[0.0002081157,0.00002507714,0.846123,0.0001219975,0.00003128336,0.00005334363,0.0007130929,0.004062889,0.0009339619,0.0004454633,0.1472464,0.00003531891],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1753238,0.0001931409,0.000588651,0.0003232532,0.00004724568,0.00009448617,0.8138868,0.0004314141,0.009111274],"genre_scores_gemma":[0.1511128,0.0002394351,0.00216282,0.00007082463,0.0000438398,0.0001990752,0.8412095,0.0002417394,0.004719913],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1303944,"threshold_uncertainty_score":0.2592708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03573427533706017,"score_gpt":0.298086945757374,"score_spread":0.2623526704203138,"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."}}