{"id":"W3047576509","doi":"","title":"The Canadian High Arctic Ionospheric Network (CHAIN)","year":2009,"lang":"en","type":"article","venue":"UCL Discovery (University College London)","topic":"Methane Hydrates and Related Phenomena","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Chain (unit); Arctic; Ionosphere; The arctic; Computer science; Geography; Meteorology; Geology; Oceanography; Geophysics; Astronomy; Physics","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":[0.001515428,0.0006850267,0.0004537085,0.002462639,0.004648725,0.002587538,0.00104756,0.0008163494,0.03092264],"category_scores_gemma":[0.00406716,0.0003219481,0.0003700245,0.004821542,0.000513967,0.000684718,0.001790371,0.0009400961,0.005964302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01944362,"about_ca_system_score_gemma":0.08957062,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9865299,"about_ca_topic_score_gemma":0.9917088,"domain_scores_codex":[0.9988006,0.00008617245,0.00002967268,0.0001127289,0.0005826288,0.0003881945],"domain_scores_gemma":[0.992471,0.0001971854,0.0002996139,0.0003107682,0.005261872,0.00145957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003441477,0.00003678419,0.02438986,0.0001530703,0.00005523388,0.0001039945,0.0001937652,0.001379312,0.0005296476,0.006558004,0.8969151,0.06934103],"study_design_scores_gemma":[0.00008997184,0.00003193006,0.07008544,0.0001540005,0.00004786957,0.00004832145,0.0004457454,0.002084394,0.000591401,0.001427119,0.9249429,0.0000508693],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.04054939,0.006626042,0.006498905,0.01985546,0.003774176,0.000704436,0.4742931,0.002914404,0.444784],"genre_scores_gemma":[0.2643569,0.007135516,0.02263786,0.006094042,0.0008211084,0.0005794183,0.2173565,0.001306275,0.4797125],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03092264,"threshold_uncertainty_score":0.1410739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004116075384766162,"score_gpt":0.1577113509525147,"score_spread":0.1535952755677485,"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."}}