{"id":"W6910821546","doi":"10.5065/d6gb223n","title":"HLY-05-02 Macrofauna Data. Version 1.0","year":2013,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Replicate; Abundance (ecology); Arctic; Biomass (ecology); Water column; Benthic zone; Structural basin; Sediment","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":[0.001088732,0.001549609,0.001141945,0.003212431,0.0006247576,0.001575545,0.00232238,0.001172081,0.05421245],"category_scores_gemma":[0.002814854,0.0006987849,0.0009619503,0.003887079,0.000320801,0.0008858158,0.001926706,0.0009801992,0.06113457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001555225,"about_ca_system_score_gemma":0.002293007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05082102,"about_ca_topic_score_gemma":0.08713181,"domain_scores_codex":[0.9990132,0.0001012647,0.0001028624,0.0002506713,0.0002855177,0.0002464513],"domain_scores_gemma":[0.997969,0.0002802075,0.0003070965,0.0004171501,0.000803582,0.0002229494],"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":[0.000282045,0.00010681,0.01816684,0.0009680389,0.0001096109,0.00007590073,0.0001520854,0.001183627,0.001063013,0.0004781248,0.9657344,0.01167947],"study_design_scores_gemma":[0.0003326054,0.00006243024,0.05607045,0.0002187083,0.00005095719,0.0000643501,0.000212169,0.001666289,0.001325702,0.000550068,0.9393904,0.00005589533],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009960817,0.0000245716,0.0001297436,0.00001431362,0.00001045663,0.00001944921,0.9976682,0.0006029379,0.0005342544],"genre_scores_gemma":[0.001194194,0.00001697756,0.0004090155,0.0000229136,0.000005104823,0.000105045,0.9974598,0.00009744641,0.000689527],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05421245,"threshold_uncertainty_score":0.1813587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09342293781246294,"score_gpt":0.362528516085836,"score_spread":0.269105578273373,"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."}}