{"id":"W3047096992","doi":"10.3390/rs12152486","title":"Proof of Concept for Sea Ice Stage of Development Classification Using Deep Learning","year":2020,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of Calgary; University of Manitoba","funders":"","keywords":"Sea ice; Artificial neural network; Arctic; Categorization; Synthetic aperture radar; Arctic ice pack; Computer science; Remote sensing; Geology; Artificial intelligence; Climatology; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001583756,0.00007504897,0.0001587481,0.0000254614,0.0001071208,0.000007841326,0.00005286296,0.00004116896,0.00002823908],"category_scores_gemma":[0.0001211505,0.00007092085,0.00003709622,0.0001219765,0.00006166163,0.00006746,0.000007873528,0.00008270642,0.000001164964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007286232,"about_ca_system_score_gemma":0.00009544734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000202558,"about_ca_topic_score_gemma":0.00004496362,"domain_scores_codex":[0.9992655,0.00004042924,0.0002552441,0.0001432817,0.0001483526,0.0001471802],"domain_scores_gemma":[0.9994587,0.0001208152,0.0002163566,0.00005696427,0.00009126726,0.00005583679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006973101,0.000004274129,0.006863221,0.0002908554,0.00003089064,0.000002216763,0.004714642,0.09723955,0.004373097,0.00001669027,0.000001941969,0.8863929],"study_design_scores_gemma":[0.0001544094,0.0000559794,0.002434345,0.00004985484,0.00001497001,0.000003294111,0.001947458,0.9880158,0.006410702,0.00001960658,0.0008111555,0.00008240265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5653855,0.00003633127,0.434018,0.00008047411,0.00003845345,0.000126219,0.000006400586,0.000010308,0.0002983163],"genre_scores_gemma":[0.8524146,0.000003155754,0.147402,0.00005635863,0.0000355199,1.409093e-9,0.00004773156,0.000003705789,0.00003686973],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8907763,"threshold_uncertainty_score":0.2892068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04499805701483151,"score_gpt":0.2474443498731874,"score_spread":0.2024462928583559,"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."}}