{"id":"W4394503080","doi":"10.6084/m9.figshare.24995255.v1","title":"Urban Calgary GNSS Skyplots data","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"GNSS applications; Geography; Environmental science; Computer science; Global Positioning System; Telecommunications","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":[0.00007116511,0.0002911512,0.0002692105,0.000110441,0.0001016267,0.0003028185,0.001177737,0.0003180926,0.4399376],"category_scores_gemma":[0.0003757328,0.0002162513,0.00007037666,0.0001899421,0.000008509405,0.0001411197,0.000164038,0.0006283378,0.2654935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003360427,"about_ca_system_score_gemma":0.0001662756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001810159,"about_ca_topic_score_gemma":0.005817479,"domain_scores_codex":[0.9983692,0.00005499636,0.0002080177,0.0006725986,0.0003427295,0.0003524508],"domain_scores_gemma":[0.9980804,0.0001559807,0.00007874146,0.001474151,0.00002594387,0.0001847459],"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":[0.000004061847,0.000004208364,0.000009119618,0.0003699905,0.00002899777,0.0004477907,0.000005257171,0.000003819514,6.980807e-9,1.017672e-8,0.9879174,0.01120931],"study_design_scores_gemma":[0.00004867886,0.00002895085,0.0006952952,0.001722444,0.00004492535,0.00005112304,0.000003007512,0.002192132,2.564144e-7,0.000005997759,0.9948903,0.0003169151],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000001141926,0.003787117,1.027539e-8,0.00004310093,0.0007504676,0.0001266793,0.9919998,0.0001087396,0.003182931],"genre_scores_gemma":[0.000005499924,0.00009275036,0.00001942438,0.0003512604,0.001215458,3.58408e-7,0.9974634,0.000009620187,0.0008422498],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1744442,"threshold_uncertainty_score":0.8818473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0702040497542245,"score_gpt":0.2616439321645235,"score_spread":0.191439882410299,"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."}}