{"id":"W2110562472","doi":"10.1109/oceans.1995.526816","title":"Global requirements and markets for marine environmental monitoring","year":2002,"lang":"en","type":"article","venue":"","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Market analysis; Business; Government (linguistics); Market research; Marine industry; Industrial organization; Environmental resource management; Marketing; Environmental science","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":[0.002613111,0.0003236071,0.0002496359,0.001624495,0.001017867,0.004353837,0.0006230256,0.00171859,0.0175046],"category_scores_gemma":[0.006328095,0.0002428704,0.0004528612,0.001417697,0.001358592,0.006098683,0.001979429,0.001184372,0.00117561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002230557,"about_ca_system_score_gemma":0.001010227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002964968,"about_ca_topic_score_gemma":0.005665278,"domain_scores_codex":[0.9986247,0.0003079335,0.00006208239,0.0001984205,0.000598106,0.0002087988],"domain_scores_gemma":[0.994913,0.002394959,0.0008004988,0.0002472523,0.001159838,0.0004845582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0005957735,0.0002477396,0.1002002,0.0005997269,0.00007138425,0.002036143,0.004069013,0.01030841,0.01620244,0.6009817,0.0278918,0.2367957],"study_design_scores_gemma":[0.00009058739,0.0007540506,0.2907753,0.0006812552,0.00009368738,0.003781349,0.01851871,0.02105549,0.00717303,0.1978627,0.4590287,0.0001851053],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4794367,0.004125478,0.009004203,0.01887216,0.00008815753,0.0001270166,0.001372903,0.0001360267,0.4868374],"genre_scores_gemma":[0.9810894,0.001224188,0.003375659,0.001108847,0.0001027826,0.00008263451,0.0006536994,0.000064787,0.01229794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0175046,"threshold_uncertainty_score":0.0585587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02862533229145366,"score_gpt":0.257602159623383,"score_spread":0.2289768273319293,"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."}}