{"id":"W142337309","doi":"","title":"Adding Value to Information Systems Using Free Data","year":2007,"lang":"en","type":"article","venue":"˜The œopen source business resource","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Value (mathematics); Computer science; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.003307295,0.0004763065,0.0004667833,0.0005951728,0.001105705,0.004631302,0.01082257,0.0001920303,0.0001162193],"category_scores_gemma":[0.0009216663,0.0003706587,0.00005764394,0.003600043,0.000149593,0.007385661,0.01355036,0.0002710008,0.00101491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00011044,"about_ca_system_score_gemma":0.00007821189,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01414745,"about_ca_topic_score_gemma":0.0004903356,"domain_scores_codex":[0.9964533,0.00003606486,0.0009590543,0.0006933828,0.0009595001,0.0008987007],"domain_scores_gemma":[0.9938955,0.0001938008,0.0006739569,0.004474682,0.0006977909,0.00006427823],"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":[0.001672101,0.0004805155,0.01265286,0.002143362,0.0003361406,0.00008197475,0.001501231,0.1602092,0.001812438,0.04921282,0.5080738,0.2618235],"study_design_scores_gemma":[0.0003963049,0.000003817418,0.003874335,0.0003175175,0.00009594957,0.00003974828,0.001410707,0.04256452,0.00001389132,0.00008960078,0.9506394,0.0005542104],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07398841,0.0005865115,0.7698134,0.003721321,0.003379886,0.004664764,0.0002585833,0.0009488737,0.1426382],"genre_scores_gemma":[0.9755789,0.000008401861,0.002870835,0.01192241,0.006076944,0.00005493562,0.001466102,0.0001952145,0.001826246],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9015905,"threshold_uncertainty_score":0.9998745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1029736724803946,"score_gpt":0.3123360375839506,"score_spread":0.209362365103556,"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."}}