{"id":"W2765287835","doi":"10.1109/oceanse.2017.8084984","title":"Development and integration of digital technologies addressed to raise awareness and access to European underwater cultural heritage. An overview of the H2020 i-MARECULTURE project","year":2017,"lang":"en","type":"article","venue":"OCEANS 2017 - Aberdeen","topic":"Maritime and Coastal Archaeology","field":"Arts and Humanities","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Cultural heritage; Underwater; Computer science; Engineering; Architectural engineering; Telecommunications; Engineering management; Political science; Geology; Oceanography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008712287,0.0001403839,0.0001941689,0.00004545736,0.000418307,0.0003665389,0.0005293211,0.00003088334,0.00002254484],"category_scores_gemma":[0.00005468091,0.00008041031,0.00002471368,0.0000205748,0.0003857244,0.0005823491,0.0009889419,0.00007332514,0.000002716056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007186116,"about_ca_system_score_gemma":0.00002651869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003006969,"about_ca_topic_score_gemma":0.006172374,"domain_scores_codex":[0.99933,0.00003382014,0.0001844401,0.0002097356,0.0001050344,0.0001369554],"domain_scores_gemma":[0.9993989,0.00001201982,0.0001205564,0.0003136186,0.0001200393,0.00003485176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005505129,0.000452341,0.03522095,0.001100028,0.0003231769,0.00003103769,0.4297478,0.000005644598,0.008527566,0.0476293,0.01803445,0.4583771],"study_design_scores_gemma":[0.001603008,0.001183787,0.1483354,0.001329207,0.0001225219,0.00002704541,0.05655996,0.00004021668,0.02317013,0.004596164,0.7618206,0.001211955],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812087,0.0001356528,0.00001695976,0.001958312,0.00007586731,0.000433769,0.0001188721,0.00004049583,0.01601134],"genre_scores_gemma":[0.9973484,0.00005623689,0.000224158,0.00007472252,0.00002851627,0.00001250408,0.0000256224,0.00001075134,0.00221911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7437861,"threshold_uncertainty_score":0.3534543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.155324528965378,"score_gpt":0.3358145836454358,"score_spread":0.1804900546800578,"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."}}