{"id":"W2994022091","doi":"","title":"Oceans 2.0 API: Programmatic access to Ocean Networks Canada's sensor data.","year":2017,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Data access; Computer science; Wireless sensor network; Remote sensing; Data science; Geography; Database; Computer network","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":[0.001504777,0.002158421,0.000818814,0.002140871,0.0008686925,0.002311446,0.004068746,0.0008607543,0.05858623],"category_scores_gemma":[0.005383061,0.001599915,0.001049402,0.002485804,0.001006542,0.002112006,0.003732605,0.002022339,0.02698959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004602497,"about_ca_system_score_gemma":0.01089353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4430059,"about_ca_topic_score_gemma":0.4568069,"domain_scores_codex":[0.9991586,0.00005222527,0.00004317991,0.0001278409,0.000417698,0.0002004137],"domain_scores_gemma":[0.9983936,0.0002682813,0.00006582058,0.0003328788,0.0007167318,0.0002226448],"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":[0.0006830042,0.00006459629,0.004164609,0.0005680569,0.000204003,0.000271082,0.0005585208,0.005064637,0.008067375,0.01062306,0.916808,0.05292313],"study_design_scores_gemma":[0.0004997017,0.00004039441,0.005643391,0.0002504397,0.00008693142,0.0001923247,0.00034772,0.08104312,0.02546112,0.01215346,0.8740177,0.0002636613],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.004580628,0.0004714963,0.1196098,0.0005919008,0.0002886242,0.0004945816,0.1195396,0.7136754,0.04074802],"genre_scores_gemma":[0.144393,0.001721522,0.1677302,0.001955781,0.0001608652,0.001967009,0.3725479,0.2370145,0.07250924],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.4430059,"threshold_uncertainty_score":0.8808547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04743536572428945,"score_gpt":0.3251813495384059,"score_spread":0.2777459838141164,"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."}}