{"id":"W4398265987","doi":"10.7910/dvn/ii5jzg/ujisom","title":"MSP_F_70_NFL_4_33.xlsx","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Context (archaeology); Resolution (logic); Computer science; Geography; Artificial intelligence; 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":[],"category_scores_codex":[0.001263985,0.004730337,0.002598824,0.004776158,0.00127466,0.004532578,0.005652096,0.004406229,0.2851761],"category_scores_gemma":[0.009619373,0.001433939,0.002169349,0.008707749,0.0009644892,0.002916449,0.003170688,0.002564837,0.3227201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002301868,"about_ca_system_score_gemma":0.002681315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01815362,"about_ca_topic_score_gemma":0.02623068,"domain_scores_codex":[0.9986281,0.0001916275,0.0001406886,0.0003751799,0.0003618827,0.0003024775],"domain_scores_gemma":[0.9969931,0.001085606,0.000224293,0.00077634,0.0006344846,0.0002863127],"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":[0.00003740652,0.00002435826,0.0002580012,0.0007141799,0.00001884119,0.00001119079,0.00001395292,0.000340854,0.00005586988,0.0003741522,0.9967524,0.001398855],"study_design_scores_gemma":[0.0005746385,0.00004140988,0.001913398,0.0004145248,0.00002841601,0.0000761284,0.00008902307,0.001041797,0.0006114243,0.002977935,0.9921871,0.00004415379],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001048343,0.00008529381,0.00007083565,0.00007425658,0.00002741832,0.000009599315,0.997749,0.0008984421,0.0009802135],"genre_scores_gemma":[0.0004780439,0.00009904888,0.000356435,0.00007248762,0.00001358143,0.00008267639,0.9979014,0.0002464467,0.0007497962],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7148239,"threshold_uncertainty_score":0.9540091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01453785021965989,"score_gpt":0.2085162319873152,"score_spread":0.1939783817676553,"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."}}