{"id":"W2769830113","doi":"10.1080/2154896x.2017.1394108","title":"Exploring the user-producer interface of weather and sea ice information for Arctic marine mobilities: a dedicated session at the Ninth International Congress on Arctic Social Sciences (ICASS)","year":2017,"lang":"en","type":"article","venue":"The Polar Journal","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Ninth; Arctic; Session (web analytics); Mobilities; Oceanography; The arctic; Meteorology; Geography; Political science; Environmental science; Climatology; Business; Sociology; Advertising; Geology; Social science","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.02306405,0.001018555,0.0006764309,0.0009283876,0.003472538,0.01250097,0.001192356,0.003037828,0.01625488],"category_scores_gemma":[0.02952401,0.0005957116,0.0009912683,0.0009422307,0.002221324,0.01141948,0.00675957,0.002364375,0.002298311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002407083,"about_ca_system_score_gemma":0.002452375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005568628,"about_ca_topic_score_gemma":0.006646245,"domain_scores_codex":[0.9880792,0.01015629,0.0002256171,0.0003911668,0.0006673743,0.0004803184],"domain_scores_gemma":[0.9712778,0.02442246,0.0002905529,0.0007081013,0.002212484,0.001088683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.003035781,0.001529601,0.03412741,0.003169245,0.0001501821,0.003447395,0.621975,0.003033372,0.02337126,0.05051945,0.08983209,0.1658092],"study_design_scores_gemma":[0.000401794,0.001141621,0.01935435,0.001712987,0.0002873495,0.0008632499,0.2377107,0.02765495,0.01312583,0.02432686,0.6730732,0.0003471025],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6276626,0.00334394,0.1888621,0.04659187,0.00190848,0.002595637,0.002465166,0.003349561,0.1232205],"genre_scores_gemma":[0.8801744,0.0016931,0.0811174,0.003754361,0.0004121697,0.001711163,0.001760134,0.001818819,0.02755843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9965274,"threshold_uncertainty_score":0.1219758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.11140383768039,"score_gpt":0.3797982888635518,"score_spread":0.2683944511831619,"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."}}