{"id":"W6931723265","doi":"10.5683/sp2/ndr2lx","title":"Jobber's House -- Fish Creek Park -- Laser Scanning -- Metadata -- 2019","year":2019,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Fish <Actinopterygii>; Laser scanning; Metadata; Scanner; Fish pond; National park","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008237197,0.002029624,0.0012563,0.002547462,0.001081845,0.001795391,0.002390179,0.001350351,0.02584682],"category_scores_gemma":[0.002217895,0.0006143826,0.0009208416,0.004333611,0.000683605,0.001185069,0.001996681,0.001321075,0.0755355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001698601,"about_ca_system_score_gemma":0.002430544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07073644,"about_ca_topic_score_gemma":0.1777009,"domain_scores_codex":[0.9988342,0.00009733688,0.00008350299,0.0003882043,0.00038608,0.0002107737],"domain_scores_gemma":[0.9987948,0.0001137713,0.0001139147,0.0003641365,0.0004667604,0.0001465598],"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":[0.00009071189,0.00002992125,0.002918891,0.0003400799,0.00002377057,0.00005434288,0.00007173697,0.0003362783,0.000602005,0.0004186952,0.9883546,0.006759045],"study_design_scores_gemma":[0.00004761629,0.00001830684,0.01266219,0.0001503556,0.00001718696,0.0001150461,0.0002125429,0.0004608072,0.001155109,0.0005707876,0.9845507,0.00003936604],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000744976,0.0001034069,0.0002315196,0.000053512,0.00004617186,0.0000168098,0.9962772,0.000924596,0.001601836],"genre_scores_gemma":[0.0007393833,0.000033343,0.0003930938,0.00001564273,0.000004850765,0.00002835914,0.9978927,0.00007509314,0.0008177249],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07073644,"threshold_uncertainty_score":0.1406494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03350238064315578,"score_gpt":0.2833337248521851,"score_spread":0.2498313442090293,"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."}}