{"id":"W1905893694","doi":"10.1111/jpim.12294","title":"A New Method for Identifying Recombinations of Existing Knowledge Associated with High‐Impact Innovation","year":2015,"lang":"en","type":"article","venue":"Journal of Product Innovation Management","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"Army Research Laboratory","keywords":"Computer science; Variance (accounting); Work (physics); Data science; Field (mathematics); Business; Mathematics","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01178284,0.0009093158,0.0009451457,0.0309664,0.001707615,0.00493739,0.001527194,0.001485711,0.005375089],"category_scores_gemma":[0.08976186,0.000480632,0.001464657,0.02565121,0.00162768,0.005347277,0.00314205,0.001648224,0.001186493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001575807,"about_ca_system_score_gemma":0.002658937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004552983,"about_ca_topic_score_gemma":0.00674876,"domain_scores_codex":[0.9867139,0.003968578,0.001880357,0.002994122,0.003962796,0.0004801662],"domain_scores_gemma":[0.9336382,0.04154527,0.01061898,0.007539554,0.005759393,0.0008987006],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005539762,0.0003811314,0.3341293,0.001188543,0.001326632,0.000464552,0.006101392,0.009620185,0.01279686,0.0747081,0.006514321,0.5522149],"study_design_scores_gemma":[0.0002988802,0.0007328524,0.3897693,0.000645716,0.001081239,0.003643289,0.005992258,0.2991799,0.02270588,0.197881,0.07718278,0.0008869887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1105841,0.0007614624,0.8686544,0.0006492857,0.0001678413,0.001174663,0.004700792,0.001241073,0.01206635],"genre_scores_gemma":[0.4520806,0.0004333727,0.5393532,0.00009034204,0.0001451224,0.001944467,0.002760981,0.0001774744,0.003014422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9882172,"threshold_uncertainty_score":0.06231433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.80167535965227,"score_gpt":0.6487605366471354,"score_spread":0.1529148230051346,"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."}}