{"id":"W6888715475","doi":"10.21966/1ty5-e654","title":"Eelgrass Extent - Coastal British Columbia","year":2016,"lang":"en","type":"dataset","venue":"Hakai Institute","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bathymetry; Polygon (computer graphics); Geospatial analysis; Shapefile; Zostera marina; Sample (material); Geographic information system; Seagrass","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":[0.000163037,0.0006496685,0.0004605431,0.003121799,0.001182911,0.001635084,0.0009599819,0.0002287855,0.02785125],"category_scores_gemma":[0.001216746,0.0003071683,0.0002614434,0.008139413,0.0002070645,0.0004318696,0.0007004834,0.0006107335,0.01021681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006685779,"about_ca_system_score_gemma":0.007279503,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9305061,"about_ca_topic_score_gemma":0.9735792,"domain_scores_codex":[0.9996977,0.00001118617,0.00002411264,0.00007813619,0.0001155517,0.00007330723],"domain_scores_gemma":[0.9986463,0.00004781961,0.00008234735,0.0001382833,0.000962374,0.0001228421],"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":[0.0001845004,0.00004369924,0.05342174,0.000500072,0.00008091232,0.0001994176,0.0004225349,0.001462377,0.0008225257,0.001676038,0.888084,0.05310223],"study_design_scores_gemma":[0.00004739727,0.000008242563,0.1605443,0.000256905,0.00003130361,0.0000939778,0.00104882,0.00173952,0.001048801,0.0003843203,0.8347409,0.00005548272],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01545168,0.0001476927,0.0003364982,0.00007895708,0.00002744685,0.00005182074,0.965876,0.0005651913,0.01746483],"genre_scores_gemma":[0.04047518,0.0002450035,0.00164585,0.00005477455,0.000005821411,0.0002074141,0.9386337,0.0002186019,0.01851375],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06949395,"threshold_uncertainty_score":0.1398064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01655038975220688,"score_gpt":0.2499827423470035,"score_spread":0.2334323525947966,"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."}}