{"id":"W2739031277","doi":"10.2495/dne-v12-n4-516-524","title":"Conceptual modelling of upstream offshore seaweed supply","year":2018,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Outsourcing and Supply Chain Management","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Submarine pipeline; Upstream (networking); Marine engineering; Environmental science; Engineering; Environmental resource management; Geotechnical engineering; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005181035,0.0001375346,0.000220365,0.0003932834,0.00005988581,0.0001315826,0.0003923428,0.0001205902,0.00007132749],"category_scores_gemma":[0.00006781191,0.0001157744,0.0001013271,0.0001389679,0.0001291908,0.0005181934,0.00009950373,0.0002923388,0.000008048103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003364956,"about_ca_system_score_gemma":0.00002890516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000489133,"about_ca_topic_score_gemma":0.0000182736,"domain_scores_codex":[0.9988524,0.00001442058,0.0004184182,0.0001324623,0.0004335737,0.0001487508],"domain_scores_gemma":[0.9985049,0.00007933554,0.0004763566,0.00009190117,0.0008290784,0.00001845442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004606532,0.001257287,0.1282774,0.0003215027,0.003933036,0.0005764584,0.004867067,0.3676057,0.002761069,0.3476084,0.04825472,0.08993093],"study_design_scores_gemma":[0.002296221,0.0002212834,0.001891108,0.0003844627,0.0002455807,0.0000820052,0.002216427,0.9236445,0.0004198386,0.02068631,0.04748492,0.0004273277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4734209,0.0006442032,0.5096741,0.003951482,0.003228057,0.0002265491,0.00001668147,0.00003901703,0.008798926],"genre_scores_gemma":[0.9925897,0.00007638424,0.004345443,0.0007677187,0.001963139,6.551774e-7,0.0000123033,0.00001668585,0.0002280362],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5560389,"threshold_uncertainty_score":0.4721141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01779030839681312,"score_gpt":0.2329905633552591,"score_spread":0.215200254958446,"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."}}