{"id":"W6906595644","doi":"10.17605/osf.io/7savj","title":"Biol 548T project","year":2022,"lang":"en","type":"other","venue":"Open Science Framework","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Work (physics); Process (computing); Data collection; Natural (archaeology)","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005038228,0.001468378,0.00104435,0.003117027,0.002023891,0.005751015,0.003014885,0.001751163,0.433854],"category_scores_gemma":[0.01316842,0.0006749652,0.00138951,0.003160459,0.0009251001,0.002978486,0.006740264,0.002228359,0.4371239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001954513,"about_ca_system_score_gemma":0.005304398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01585448,"about_ca_topic_score_gemma":0.02035801,"domain_scores_codex":[0.99715,0.0005096536,0.0001094226,0.0006209879,0.001188456,0.0004214587],"domain_scores_gemma":[0.9952598,0.0008136854,0.000187547,0.001092662,0.00142162,0.00122465],"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":[0.0000775075,0.00001343698,0.0003957754,0.00009839771,0.00001043743,0.00001701607,0.00007845652,0.00005808106,0.0001981942,0.004548252,0.9751428,0.0193617],"study_design_scores_gemma":[0.00002349742,0.000009541459,0.0005765695,0.00005626061,0.000007235806,0.0000266316,0.00005093334,0.0001480535,0.0001447712,0.002124085,0.9968226,0.000009740537],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001534008,0.001031185,0.01479411,0.007280414,0.003296121,0.0002725223,0.5756375,0.07085507,0.3252991],"genre_scores_gemma":[0.008404347,0.0008231961,0.01910698,0.004666415,0.0006288148,0.0008539599,0.6728443,0.05524598,0.237426],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.566146,"threshold_uncertainty_score":0.8075385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05324694073044119,"score_gpt":0.4029139516073057,"score_spread":0.3496670108768645,"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."}}