{"id":"W2164032481","doi":"10.1016/j.cageo.2011.06.009","title":"Establishing a sustainable and cross-boundary geospatial cyberinfrastructure to enable polar research","year":2011,"lang":"en","type":"article","venue":"Computers & Geosciences","topic":"Polar Research and Ecology","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"U.S. Geological Survey","keywords":"Cyberinfrastructure; Geospatial analysis; Data science; Computer science; Earth science; Field (mathematics); Process (computing); Earth observation; Remote sensing; Satellite; Geography; Geology; 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":[0.01455847,0.0003670879,0.0003377963,0.002395686,0.003269206,0.01132495,0.001943487,0.00289151,0.006544279],"category_scores_gemma":[0.02064767,0.0004861066,0.0004490196,0.00136351,0.00411087,0.02086774,0.01952489,0.003148575,0.002408308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001843172,"about_ca_system_score_gemma":0.007959087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001333234,"about_ca_topic_score_gemma":0.001445336,"domain_scores_codex":[0.9934297,0.003067894,0.0005463347,0.0007330677,0.001628905,0.0005940284],"domain_scores_gemma":[0.9775175,0.004699274,0.002422843,0.006098618,0.005143892,0.004117738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001655509,0.0006898367,0.01570124,0.0003489074,0.00007515098,0.0005508143,0.005104629,0.01071363,0.02298039,0.6471851,0.01953844,0.2769463],"study_design_scores_gemma":[0.0001066238,0.0005018514,0.01234309,0.0009804758,0.000056368,0.0008683999,0.0151223,0.0531533,0.01838813,0.477417,0.4208885,0.0001740106],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09205628,0.0007067494,0.7940136,0.0217972,0.000618042,0.0007777255,0.0001359105,0.001719623,0.08817493],"genre_scores_gemma":[0.5436928,0.0005532465,0.4426849,0.001532068,0.000245987,0.0005875198,0.0003616557,0.0002238883,0.01011796],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01455847,"threshold_uncertainty_score":0.07699353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02915752121784142,"score_gpt":0.3075771165807982,"score_spread":0.2784195953629567,"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."}}