{"id":"W6963380184","doi":"10.21966/kqzp-f639","title":"Spatial extent of surface canopy kelp derived from fixed-wing surveys (2020-2022), Central Coast, British Columbia, Canada","year":2020,"lang":"en","type":"dataset","venue":"Hakai Institute","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kelp; Kelp forest; Canopy; Aerial photography; Aerial survey; Habitat","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":[0.0002272714,0.0005456905,0.0002808245,0.002942578,0.001086025,0.0009304123,0.0008224683,0.0002069972,0.008710215],"category_scores_gemma":[0.0007266444,0.0003158055,0.0002742028,0.006412498,0.0001631824,0.0002559032,0.0004223383,0.0003501816,0.002489814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009848401,"about_ca_system_score_gemma":0.01440819,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9947165,"about_ca_topic_score_gemma":0.998026,"domain_scores_codex":[0.9996988,0.00001088813,0.00001917176,0.00006770081,0.0001239519,0.00007951524],"domain_scores_gemma":[0.9983064,0.00003481396,0.0000866277,0.00005137032,0.001350129,0.0001706885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003172667,0.0001293848,0.5781749,0.000810674,0.0002674068,0.0004566445,0.001099468,0.004295797,0.004169154,0.0006768279,0.2961152,0.1134873],"study_design_scores_gemma":[0.00002102917,0.00001078404,0.9575267,0.0001337573,0.0000302987,0.00005320621,0.0006867555,0.001590315,0.0004067732,0.00003561973,0.03947898,0.00002580576],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.2405437,0.0007849204,0.001186074,0.000167894,0.00004250732,0.0001998905,0.727897,0.0004349923,0.02874297],"genre_scores_gemma":[0.4128152,0.00114852,0.005955221,0.0001782857,0.00001459823,0.0003078862,0.5374184,0.0001673044,0.04199445],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.009848401,"threshold_uncertainty_score":0.07145548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01291534923971248,"score_gpt":0.2135274574033611,"score_spread":0.2006121081636486,"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."}}