{"id":"W4282554229","doi":"10.20935/al5393","title":"Search and Rescue as an Instrument of Externalisation: A Report from the Central Mediterranean Sea, 2013 to 2017","year":2022,"lang":"en","type":"article","venue":"Academia Letters","topic":"Maritime Security and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Interdiction; Search and rescue; Euros; Mediterranean sea; European union; Geography; Computer science; Mediterranean climate; Operations research; Environmental resource management; Business; International trade; Engineering; Archaeology; Artificial intelligence; Economics; Humanities","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":[],"consensus_categories":[],"category_scores_codex":[0.001277119,0.0003274856,0.0003172782,0.001483842,0.0007446305,0.002235146,0.0004724086,0.000496205,0.002696511],"category_scores_gemma":[0.002785041,0.0001603656,0.0002363915,0.002661167,0.001167673,0.00111549,0.002351166,0.0005658015,0.0007303279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004422338,"about_ca_system_score_gemma":0.00449476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1032061,"about_ca_topic_score_gemma":0.1263811,"domain_scores_codex":[0.9988802,0.0001015344,0.0001054685,0.0001209763,0.0005550977,0.0002366827],"domain_scores_gemma":[0.9982298,0.0001476991,0.0006097276,0.00009240147,0.0007566201,0.0001637291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004606457,0.00007985353,0.6782526,0.001809185,0.0001904043,0.001939396,0.02891336,0.002137095,0.001339354,0.01040491,0.07954417,0.194929],"study_design_scores_gemma":[0.000008186164,0.00008608591,0.7548123,0.0004760309,0.00003167015,0.0003764172,0.02701447,0.0003437724,0.0005715771,0.000373942,0.2158719,0.00003372729],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9001449,0.007988657,0.000635773,0.004487908,0.0003084306,0.00009630243,0.009590933,0.0001037267,0.07664351],"genre_scores_gemma":[0.9624476,0.006666529,0.0005364457,0.0009028058,0.0001835335,0.00009083143,0.005996988,0.00007382311,0.02310136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1032061,"threshold_uncertainty_score":0.2052107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04660286777845996,"score_gpt":0.3153691794726538,"score_spread":0.2687663116941938,"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."}}