{"id":"W7075375830","doi":"","title":"Material Traces: mapping habitat loss in northern British Columbia","year":2016,"lang":"en","type":"other","venue":"Arca (British Columbia Electronic Library Network)","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Habitat; Natural (archaeology); Ectotherm; Fishing","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":[0.0002992532,0.0002832262,0.0001846498,0.003775519,0.001582654,0.001668582,0.0008163938,0.0003725082,0.01154948],"category_scores_gemma":[0.002038547,0.0001783997,0.0001529464,0.008658351,0.0004316906,0.0004685991,0.001200574,0.0003588774,0.002214528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005986212,"about_ca_system_score_gemma":0.01195203,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9838172,"about_ca_topic_score_gemma":0.9945903,"domain_scores_codex":[0.999743,0.00002185005,0.0000145332,0.00004523114,0.0001142383,0.00006103093],"domain_scores_gemma":[0.9987458,0.0001039682,0.00007675488,0.00009496745,0.0008401683,0.0001382715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002985773,0.00010739,0.3867267,0.000561347,0.0001151073,0.0007492928,0.006592828,0.006558807,0.001881549,0.002437046,0.30817,0.2858014],"study_design_scores_gemma":[0.00002220219,0.00001495896,0.7155879,0.0004227747,0.00006313377,0.0001460416,0.01330329,0.006665618,0.0009572074,0.0007984663,0.2619617,0.00005673974],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6838199,0.002582517,0.003584133,0.001501362,0.0001133965,0.000297739,0.1807948,0.0009899588,0.1263162],"genre_scores_gemma":[0.7810069,0.002002539,0.006382822,0.0002755059,0.0000233912,0.0002847333,0.08102769,0.0004393064,0.1285572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01618278,"threshold_uncertainty_score":0.04343325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007846611975588435,"score_gpt":0.1577959016635965,"score_spread":0.1499492896880081,"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."}}